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Self-piercing rivets (SPR) are efficient and economical joining methods used in the manufacturing of lightweight automotive bodies. The finite element method (FEM) is a potentially effective way to assess the joining process of SPRs. However, uncertain parameters could lead to significant mismatches between the FEM predictions and physical tests. Thus, a sensitivity study on critical model parameters is important to guide the high-fidelity modeling of the SPR insertion process. In this paper, an axisymmetric FEM model is constructed to simulate the insertion process of the SPR using LS-DYNA/explicit. Then, several surrogate models are evaluated and trained using machine learning methods to represent the relations between selected inputs (e.g., material properties, interfacial frictions, and clamping force) and outputs (cross-section dimensions).

Weld lines can significantly reduce ultimate tensile strength (UTS) and fracture strain of talc filled polypropylene (PP). In this paper, two different injection molding tests were completed. First, an injection mold with triangular inserts was built to study the influence of meeting angles on material properties at the weld line region. Tensile samples were cut at different locations along the weld line on the injection molded plaques. The test results showed that both UTS and fracture strain increase when the sample locations are away from the insert. This trend is attributed to different meeting angles. Second, standard ISO tensile bars with and without weld line were injection molded to identify the size of the weld line affected zone. A FEA model was built in ABAQUS, where the tensile sample was divided into two different regions, the solid region and the weld line affected region.

As an alternative lightweight material, chopped carbon fiber reinforced Sheet Molding Compound (SMC) composites, formed by compression molding, provide a new material for automotive applications. In the present study, the monotonic and fatigue behavior of chopped carbon fiber reinforced SMC is investigated. Tensile tests were conducted on coupons with three different gauge length, and size effect was observed on the fracture strength. Since the fiber bundle is randomly distributed in the SMC plaques, a digital image correlation (DIC) system was used to obtain the local modulus distribution along the gauge section for each coupon. It was found that there is a relationship between the local modulus distribution and the final fracture location under tensile loading. The fatigue behavior under tension-tension (R=0.1) and tension-compression (R=-1) has also been evaluated.

Weld lines occur when melt flow fronts meet during the injection molding of plastic parts. It is important to investigate the weld line because the weld line area can induce potential failure of structural application. In this paper, a weld line factor (W-L factor) was adopted to describe the strength reduction to the ultimate strength due to the appearance of weld line. There were two engineering thermoplastics involved in this study, including one neat PP and one of talc filled PP plastics. The experimental design was used to investigate four main injection molding parameters (melt temperature, mold temperature, injection speed and packing pressure). Both the tensile bar samples with/without weld lines were molded at each process settings. The sample strength was obtained by the tensile tests under two levels of testing speed (5mm/min and 200mm/min) and testing temperatures (room temperature and -30°C). The results showed that different materials had various values of W-L factor.

Self-piercing rivet (SPR) joints are a key joining technology for lightweight materials, and they have been widely used in automobile manufacturing. Manual visual crack inspection of SPR joints could be time-consuming and relies on high-level training for engineers to distinguish features subjectively. This paper presents a novel machine learning-based crack detection method for SPR joint button images. Firstly, sub-images are cropped from the button images and preprocessed into three categories (i.e., cracks, edges and smooth regions) as training samples. Then, the Artificial Neural Network (ANN) is chosen as the classification algorithm for sub-images. In the training of ANN, three pattern descriptors are proposed as feature extractors of sub-images, and compared with validation samples. Lastly, a search algorithm is developed to extend the application of the learned model from sub-images into the original button images.

Self-pierced rivet (SPR) and adhesive are two important joining technologies widely used in automobile industry, and they are often used together to form a hybrid joint. SPR and adhesives can often be used in close proximity in a component, leading to an interaction of the two joints. This interaction can influence the corrosion and noise, vibration and harshness (NVH) characteristics of the structure, as well as its strength and durability. In this paper, the stress distribution in an SPR-adhesive hybrid joint is evaluated by using the finite element method, and then compared with that in an adhesive joint. Results indicate that the stress concentrates at the edge of adhesive layer in hybrid joint and adhesive joint and around the rivet in an SPR joint. The effect of rivet is numerically investigated by either removing the rivet from the hybrid joint or changing the position of the rivet on the overlapping area.

SIF value around weld nugget changes when specimen width is different. To investigate the influence of specimen width on SIF value around weld nugget of coach peel specimen (CP), a finite element model was established in this paper. In this model, a contour integral crack was used, and the area around the nugget was treated as crack tip. Results indicated that when specimen width was below 50mm, SIF decreased rapidly with the increase of specimen width. When specimen width was larger than 50mm, SIF almost remained constant with the variation of specimen width. To further study the influences of nugget diameter and sheet thickness on the Width-SIF curves, CP specimens with different nugget diameters (5mm, 6mm and 7mm) and sheet thicknesses (1.2mm, 1.6mm and 2.0mm) were established in ABAQUS. Simulation results of all CP specimens showed a similar relationship between specimen width and SIF.