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The problem of springback is one of the most significant factors affecting the forming accuracy for aluminum 3D stretch-bending parts. In order to achieve high-efficiency and high-quality forming of such kind of structural components, the springback behaviors of the AA6082 aluminum profiles are investigated based on the flexible multi-points 3D stretch-bending process (3D FSB). Firstly, a finite element simulation model for the 3D FSB process was developed to analyze the forming procedure and the springback procedure. The forming experiments were carried out for the rectangle-section profile to verify the effectiveness of the simulation model. Secondly, the influence of tension on springback was studied, which include the pre-stretching and the post-stretching. Furthermore, the influences of the bending radius and bending sequence are revealed. The results show that: (1) The numerical model can be used to evaluate the effects of bending radius and process parameters on springback in the 3D FSB process effectively. (2) The pre-stretching has little effect on the horizontal springback reduction, but it plays a prominent role in reducing the springback in the vertical direction. (3) The increase of bending deformation in any direction will lead to an increase of springback in its direction and reduce the springback in the other direction. Besides, it reduces the relative error in both directions simultaneously. This research established a foundation to achieve the precise forming of the 3D stretch-bending parts with closed symmetrical cross-section.

Purpose This paper aims to automatically derive a 2D parametric model of the main characteristic lines of a car from images, blueprints or hand-made sketches of its side view. Then this model can be used for the further computer-aided design manipulation starting from images of the side view of a car. Design/methodology/approach The method combines different image edge detection techniques and edge removal processes with optimization techniques according to local and global constraints specific of the single curves to automatically construct a precise parametric model of the main character lines of a car from images. First, process the car image to compute the most important curves and then warp a car template model to match its feature points and curves with the ones detected in the image. Findings The paper provides method to construct parametric model from an image using maximum cover ratio to the edge points obtained by state-of-the-art edge detection algorithms. A feature points’ organization mechanism produces quadric curves to express feature curves of a product. Research limitations/implications The robustness of the presented method depends on the completeness of edge detection results and the accuracy of some key points’ registration result, so if the image is not good, the result cannot be trusted. Only side-view is considered in this paper. Additional limits in the process regard the side view verification: pictures of the front or rear view can be wrongly classified as lateral ones when they contain round lights. Practical implications This program enables designers to convert the image to geometric parametric model directly. Originality/value The method is applicable to shaded pictures, sketches and blue prints of the side view of a car. It can process a database of car images in a batch mode or a specific picture on user demand. The method classifies the cars to different categories: SUV/Wagon/Hatchback, sedan, city and coupe. The authors obtain good results for every category.

This paper presents an approach for curve driven image warping to reshape the content of an image. The warping method is realized by inverse irregular quad mesh mapping. Considering that stylists adopt a curve based approach for their product shape definition, the devised curve driven image warping can provide a good mean for rapidly changing the product shape, thus easing the evaluation of shape alternatives. Moreover, here we show that the semantically editing of automotive images can be easily implemented combining this method with the automatic identification of the semantically important character lines.

The lightweight aluminum 3D curved structure part has the characteristics of high structural strength, excellent aerodynamic performance, and flowing geometric shape. It is increasingly used in the fields of railway transportation, aerospace, and other high-end vehicle manufacture industry. However, with the increase of forming dimensions, as well as the large, thin-walled, complex forming features, it is urgent to study the precise plastic forming method for this kind of difficult-to-deform materials. Based on the new type of flexible multi-points 3D stretch-bending (3D FSB) process, the precision forming method for these hard-to-deform parts was studied in this paper. Extensive numerical simulations for the 3D FSB forming of the target parts have been performed by finite element methods. The simulation results show good agreement with the experiment results, and the max shape error of springback prediction is less than 0.3 mm. Then, based on the measured shape error of the 3D formed parts, an iterative overbending method for envelope surface of the multi-point die (MPD) is proposed to realize precise forming of the 3D curved structure parts. After four times adjustment of MPD, the simulation results show that the contour error is reduced from 1.01 to 0.06%, the maximum springback error changes from 30.16 to 1.66 mm. According to the adjustment parameters acquired in the optimization process, the actual experimental measured contour error is 0.05%, the maximum springback error is 1.41 mm, which achieved the forming requirements of the target parts and verified the effectiveness of the compensation method.

The transition metal phosphide is one of the promising bifunctional electrocatalysts for overall water splitting. Moreover, the activity of phosphide catalysts can be further enhanced by the cationic vacancy engineering.The self-growth NiThe chemical and electrocatalytic property of Ni

Most of the existing studies use constant force to reduce springback while researching stretch force. However, variable stretch force can reduce springback more efficiently. The current research on springback prediction in stretch bending forming mainly focuses on artificial neural networks combined with the finite element simulation. There is a lack of springback prediction by support vector regression (SVR). In this paper, SVR is applied to predict springback in the three-dimensional stretch bending forming process, and variable stretch force trajectory is optimized. Six parameters of variable stretch force trajectory are chosen as the input parameters of the SVR model. Sixty experiments generated by design of experiments (DOE) are carried out to train and test the SVR model. The experimental results confirm that the accuracy of the SVR model is higher than that of artificial neural networks. Based on this model, an optimization algorithm of variable stretch force trajectory using particle swarm optimization (PSO) is proposed. The springback amount is used as the objective function. Changes of local thickness are applied as the criterion of forming constraints. The objection and constraints are formulated by response surface models. The precision of response surface models is examined. Six different stretch force trajectories are employed to certify springback reduction in the optimum stretch force trajectory, which can efficiently reduce springback. This research proposes a new method of springback prediction using SVR and optimizes variable stretch force trajectory to reduce springback.

As the consumption of fossil energy from the traffic system increases, the need for 3D structural parts which provide the design engineer a lighter, stiffer, and more energy-efficient structure is required. A new flexible 3D stretch bending process (FSB) with multi-points dies (MPD) is thus being developed. This study seeks to find out the relationship between the springback error and the adjustment parameters for the FSB process. At first, the structure of flexible fundamental unit (FFU) with four degrees of freedom (DOF) MPD was designed and implemented. Then the FSB experiments with different bending radius of curvature and materials were carried out based on prototype of the flexible 3D stretch bending equipment. The experiment results show that the springback error increased linearly along the length of the workpiece. Without using the post-stretch force, the springback error declined from 7.90 % to 0.80 % by adjusting the positions of the FFU. Most importantly, the surface defects of the forming parts such as wrinkle and crack can be eliminated in this process.

The nanostructure of α phase polyoctylfluorene thin film was characterized using normal X-ray diffraction, one-dimensional out-of-plane grazing incidence X-ray diffraction and two-dimensional grazing incidence X-ray diffraction with lab diffractometer and synchrotron diffractometer. The results show that using grazing incidence X-ray diffraction the weak diffraction signal of thin film can be observed after the elimination of background signals. Incorrect (h10) diffraction signals can be collected by lab diffractometer due to its low collimation and resolution, which can be overcome by using synchrotron diffractometer with high collimation and resolution that reveal the actual microstructure of polyoctylfluorene thin film.