International Journal of Material Forming最新文献

Establishing a unified constitutive model to simulate the hot deformation behaviors, microstructure evolution and fracture behaviors under different stress states during the hot forming of titanium alloy is indispensable. The high temperature tensile tests were first carried out on different stress states of forged Ti-6Al-4 V alloy specimens to analyze the flow behaviors, microstructure evolution and fracture mechanism. The results show that the effect of temperature on fracture elongation is more significant than strain rate. High temperature and low strain rate will increase the dynamic recrystallization (DRX) volume fraction and softening effect, which inhibits the nucleation and growth of voids, thereby enhancing the plastic deformation ability of the alloy. The DRX volume fraction, grain size and stress triaxiality were introduced into the unified Gurson-Tvergaard-Needleman (GTN) damage model using the internal state variables. The parameters of GTN model were modified by the Response Surface Method (RSM) and compared with the high temperature tension. Finally, the established GTN damage model was successfully applied to finite element (FE) simulation under different stress states. The correlation coefficient R of predicted stress is 0.989, and the maximum errors of DRX volume fraction and grain size are 9.86% and 6.54%. The research results can provide a basis for the performance control in hot working of titanium alloy.

A numerical investigation on uniaxial compression tests is performed to highlight the heterogeneous nature of the deformation process. Resulting errors on the material behaviors are deduced from the obtained force versus displacement data with the assumption of homogeneous deformation. The numerical study considers a range of strain rates (from 0.01 to 0.5 (s^{-1})), Coulomb friction coefficients (up to 0.3), and elasto-viscoplastic power law behaviors. The heterogeneous nature is characterized in terms of sample shape, strain, and strain rate heterogeneities. The results show that the final shape of the sample at a given macroscopic strain is influenced not only by the friction coefficient but also by the material properties. The levels of strain and strain rate heterogeneities in the samples can be significant in some conditions, leading to large errors when exploiting the force versus displacement data with the hypothesis of homogeneous strain. The estimations of the strain rate sensitivity parameters are not significantly affected by the strain heterogeneities, but the errors on the strain hardening parameters can be as large as 40 %. The apparent strain hardening parameter appears to be artificially strain rate sensitive. Being systematically lower than the material strain hardening parameter, when measured at lower strain rates, this underestimation will induce a systematic error in the determination of material properties and should be taken into consideration.

This work presents an interpretability study with XAI tools to explain an XGBoost model for hardness prediction in the simultaneous double-frequency induction hardening. Experiments were carried out on C45 steel spur-gear. In order to explain the model, firstly, the built-in tool of the XGBoost library was used to interpret the feature importance. Then, a more advanced approach with the SHAP library was employed to highlight local and global explanations. Finally, the implementation of an interpretable surrogate model allowed to illustrate rules for prediction, making the explanation, although approximate, clear. This study proposes a relevant approach of AI to explain the results obtained by black box models which is currently a major element for the industry allowing to justify the quality of the results in a clear way. It is concluded that the model is consistent with physical principles.

4D printed hydrogels are 3D printed objects whose properties and functions are programmable. In the definition of 4D printing, the fourth dimension arises from the ability of printed structures to change their shape and/or function over time when exposed to given conditions environmental stimuli, during their post-press life. Stimulation-responsive hydrogels produced by the emerging 4D bioprinting technology are currently considered as encouraging tools for various biomedical applications due to their exciting properties such as stretchability, biocompatibility, ultra-flexibility, and printability. Using 3D printing technology, customized functional structures with controllable geometry and trigger ability can be autonomously printed onto desired biological interfaces without considering microfabrication techniques. In this review, by studying the progress in the field of hydrogels for biointerfaces, we summarized the techniques of 4D printing gels, the classification of bioinks, the design strategies of actuators. In addition, we also introduced the applications of 4D hydrogels in tissue repair, vascular grafts, drug delivery, and wearable sensors. Comprehensive insights into the constraints, critical requirements for 4D bioprinting including the biocompatibility of materials, precise designs for meticulous transformations, and individual variability in biological interfaces.

In this study, microstructure, recrystallization texture, and mechanical properties of Al/WO₃/SiC hybrid nanocomposite was investigated by electron backscatter diffraction (EBSD), analysis of orientation distribution function (ODF), and uniaxial tensile test during accumulative roll bonding (ARB) process. Microstructural observations show that the recrystallized grains are elongated in the rolling direction (RD) due to the Zener-pinning of nanoparticles at high angle grain boundaries and therefore growth is inhibited in the normal direction (ND) during the ARB process. The ODF investigation confirmed that after 5 cycles of ARB process, recrystallization is associated with nucleation of Goss, Q, and P components. When the number of ARB cycle was increased, Goss and Q recrystallization textures were eliminated, but on the other hand, the P, B and B* texture components were strongly developed. The ND-Cube and RT-Goss recrystallization texture is also formed with low intensity at the last stages. Also, the A and A^* shear textures which formed in the fifth cycle, shifted towards the Dillamor and Cu textures with increasing the number of ARB cycles. Furthermore, the samples were heated using DSC under Argon atmosphere with four different heating rates. The Kissinger, Ozawa, Boswell, and Starink methods were used to determine the recrystallization kinetics. It can be seen that recrystallization temperature and thereby activation energy (E_a) decreases with increasing the number of ARB cycles. Furthermore, the tensile strengths and elongation of the hybrid nanocomposite increased and decreased by increasing the number of ARB cycle and reached to a maximum value of 204.5Mpa and 6.1% at the end of 9th cycle, respectively.

Deep rolling is a powerful tool to increase the service life or reduce the weight of railway axles. Three fatigue-resistant increasing effects are achieved in one treatment: lower surface roughness, strain hardening and compressive residual stresses near the surface. In this work, all measurable changes introduced by the deep rolling process are investigated. A partly deep-rolled railway axle made of high strength steel material 34CrNiMo6 is investigated experimentally. Microstructure analyses, hardness-, roughness-, FWHM- and residual stress measurements are performed. By the microstructure analyses a very local grain distortion, in the range < 5 µm, is proven in the deep rolled section. Stable hardness values, but increased strain hardening is detected by means of FWHM and the surface roughness is significantly reduced by the process application. Residual stresses were measured using the XRD and HD methods. Similar surface values are proven, but the determined depth profiles deviate. Residual stress measurements have generally limitations when measuring in depth, but especially their distribution is significant for increasing the durability of steel materials. Therefore, a numerical deep rolling simulation model is additionally built. Based on uniaxial tensile and cyclic test results, examined on specimen machined from the edge layer of the railway axle, an elastic–plastic Chaboche material model is parameterised. The material model is added to the simulation model and so the introduced residual stresses can be simulated. The comparison of the simulated residual stress in-depth profile, considering the electrochemical removal, shows good agreement to the measurement results. The so validated simulation model is able to determine the prevailing residual stress state near the surface after deep rolling the railway axle. Maximum compressive residual stresses up to about -1,000 MPa near the surface are achieved. The change from the induced compressive to the compensating tensile residual stress range occurs at a depth of 3.5 mm and maximum tensile residual stresses of + 100 MPa at a depth of 4 mm are introduced. In summary, the presented experimental and numerical results demonstrate the modifications induced by the deep rolling process application on a railway axle and lay the foundation for a further optimisation of the deep rolling process.

The forming behaviour of a unidirectional non-crimp fabric (UD-NCF) consisting of polyamide stitches with a tricot-chain stitching pattern is explored. Notably, there are no stabilising tows orientated transverse to the main tow direction in this fabric, a common feature in many ‘quasi’ UD-NCFs, this allows extension of the stitch in the transverse direction under certain loading conditions. The lack of stabilising tows introduces a possible low-energy deformation mode to the UD-NCF, which is absent in biaxial fabrics and to a large extent in ‘quasi’ UD-NCFs. The in-plane shear behaviour is initially investigated using both standard ‘tightly-clamped’ picture frame tests and uniaxial bias extension tests. Preliminary results show a dramatic difference in results produced by the two test methods. During the picture frame test, fibres can be subjected to unintended tension due to sample misalignment in the picture frame rig. To mitigate error arising from this effect, the picture frame test procedure is modified in two different ways: by using an intentional pre-displacement of the picture frame rig, and by changing the clamping condition of test specimen. Results show that the modified picture frame test data contain less error than the standard ‘tightly-clamped’ test but also that the shear stiffness of the UD-NCF is notably lower when measured in the bias extension test compared to the picture frame test, mainly due to the difference in loading conditions imposed during the two tests.

The components’ lightweighting has been pursued, especially in the transport industry, for greenhouse gas reduction. Topology optimization, being able to allocate the material within a provided design space, is a mathematical method that can support the design of lightweight components, preserving, at the same time, their mechanical performances. In this paper, a standard shape of a component, specifically an automotive bracket, was topology optimized by estimating the impacts of the new designs from an eco-friendly point of view. A subtractive, an additive and a casting manufacturing process were considered as possible manufacturing routes achieving an optimized geometry of the component for each of them. The topology optimizations were performed considering each processes’ peculiarities, introduced as constraints. Same strength for a given set of loads and boundary conditions was the target of each analysis. The component’s lightening can be considered environmentally friendly just after assessing the impacts associated with all the stages of the product’ life cycle. Indeed, each phase of the product’ life cycle can be affected, differently, by the performed topology optimization taking into account the peculiarities of the employed manufacturing process. The overall considerations on the most environmentally safe strategies can, therefore, change according to the specificities of the optimized shapes. The topology optimization showed its utmost potentiality, from a sustainable point of view, if applied to additive manufacturing techniques for the advantages arisen by the capability to manufacture complex shapes benefiting also of reduction time process owing to less material to be deposited.

A large number of carbon emissions are generated in the life cycle of metal forming equipment. The movable components are the critical part of the mechanical system in the equipment, which accounts for the carbon emissions in both of manufacturing and use stages. Reducing carbon emissions of the components in the manufacturing stage by lightweight design may result in a significant increment of emissions in the use stage. To overcome the obstacle, a method of matching the mechanical system of metal forming equipment to reduce life cycle carbon emissions is proposed. The effect of the weight of the components that determine the manufacturing’s emission on the configuration of the drive units that determine the emission in the usage stage, was analyzed and quantified. Then, the drive units were reconfigured and optimized to meet the required output force and velocity with the different weights of the components to find the optimal scheme with the lowest emissions in the life cycle. The method was applied to a 2000-ton hydraulic forming equipment, and results indicate that 14.87% of the weight of the movable components can be reduced with a total carbon emissions reduction of 22.48%. The total carbon emissions were reduced by 35.94% compared to that of the movable components through the topology optimization method. The proposed matching method can assist in the low-carbon design of the mechanical system in metal forming equipment.