Automotive Science and Engineering

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Automotive design engineers face the challenging problem of developing products in highly competitive markets. In this regard, using conceptual models in the first step of automotive development seems so necessary. In this paper, to make a body in white conceptual model, an engineering approach is developed for the replacement of beam-like structures, joints, and panels in a vehicle model. The proposed replacement methodology is based on the reduced beam, joint, and panel modeling approach, which involves a geometric analysis of beam member cross-sections and a static analysis of joints. In order to validate the proposed approach, an industrial case-study is presented. Two static load cases are defined to compare the original and the concept model by evaluating the stiffness of the full vehicle under torsion and bending in accordance with the standards used by automotive original equipment manufacturer (OEM) companies. The results show high accuracy of the concept models in comparison with the original model in bending and torsional stiffness prediction.

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Connecting point of the longitudinal veins and cross-veins in wing is called Joint.  In some insect wing joints, there is a type of rubber-like protein called Resilin. Due to the low Young's modulus of this protein, its presence in the wing can help to change the shape of the wing during flight. Today, using composite structures in flying vehicles in order to achieve the desired shape of wing is considered. The purpose of this study is the multi-objective optimization of artificial wing by arranging Resilin joints in the artificial wing of Micro air vehicles (MAVs). The amount of torsion and bending of the flapping robot wings is considered as the objective function to improve the flight performance of robots. Two types of artificial wings have been investigated, and considering pareto points, the optimal arrangement of Resilin joints has been achieved.  The result of this study shows that in both wings, with the presence of Resilin in the joints, the amount of torsion has increased to 38.65 degrees.
 

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The aim of the study was to examine the deformation modes and also degradation of an adhesively bonded rectangular cross section beam used in the automotive body structure. The study included: (1) performing new experimental investigations on the three-point bend behavior of a rectangular cross section beam made by adhesive bonding method. (2) developing a finite element (FE) model to predict the mechanical load displacement behavior and also the degradation modes (i.e. delamination between the adhesive layer and beam wall). The agreement between experimental and FE results demonstrates that the investigated structural element's numerical model was created utilizing accurate assumptions. Finally, the effects of beam wall thickness and overlap length have been investigated in a parametric study using the validated FE model. It was shown that increasing the beam wall thickness resulted in delamination between the adhesive layer and beam wall.

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This paper presents an experimental study on the effect of adhesive thickness on the maximum load of adhesive joints under static and impact loading, using the double cantilever beam (DCB) test method. The DCB specimens were prepared with varying adhesive thicknesses and subjected to impact loading using a drop weight impact tester. The maximum load was recorded for each specimen. The results indicated that the maximum load of the adhesive joints increases with increasing adhesive thickness up to 5 mm, beyond which the maximum load decreases with further increase in adhesive thickness. Moreover, the failure mode of the adhesive joint was found to be strongly dependent on the adhesive thickness, with thicker adhesive layers exhibiting an adhesive failure mode but in thinner thicknesses, the adhesive mode is cohesive. These findings provide important insights into the design and optimization of adhesive joints for applications that are subject to impact loading.

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Adhesively bonded joints are a highly effective method for achieving lightweight structural designs, yet assessing their long-term durability remains a significant challenge. Creep, a time-dependent effect caused by sustained mechanical loads, can result in viscous strain within adhesive materials, potentially leading to crack formation in bonded structures over extended periods. This study investigates the creep behavior of adhesive joints under sustained tensile loads, focusing on the effects of adhesive layer thickness and the presence of adhesive fillets. Creep tests conducted over 48 hours revealed that higher load levels result in greater strain accumulation, with thicker adhesive layers showing increased susceptibility to deformation. Additionally, joints with adhesive fillets demonstrated lower creep strain, indicating enhanced resistance to sustained loads. These findings emphasize the importance of adhesive layer thickness and fillet design in optimizing the long-term performance and durability of bonded joints, offering valuable insights for applications where creep resistance is critical for joint reliability and service life.

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In lightweight body-in-white design, joints must not only provide strength but also allow for ductility and sufficient energy absorption. In this study, Single Lap Joints (SLJs) made with adhesive bonding are compared experimentally with those joined by Resistance Spot Welding (RSW) in low-carbon steel sheets. The influence of overlap length (15 and 25 mm) and weld number (one or two spots) is examined. Tensile force–displacement tests, conducted at room temperature with a crosshead speed of 1 mm/min, revealed that extending the overlap from 15 to 25 mm improved the peak load, final displacement, and fracture energy of the adhesive joints. Among the tested configurations, double spot welds (2RSW) provided the greatest capacity and toughness.  However, adhesive joints with a 25 mm overlap (AB25) exhibited higher strength than single spot welds (1RSW), while their ductility was comparable. The observed failure modes varied across the joint types. In resistance spot welds, failure occurred mainly through button pull-out, whereas adhesive joints exhibited a mixed adhesive–cohesive failure mode.  In contrast, the 2RSW specimens displayed pull-out and necking sequences, reflecting load sharing between the weld nuggets. Overall, the findings suggest straightforward design guidelines. When maximum strength and energy absorption are required, two Spot Welds (2RSW) are the best choice. On the other hand, AB25 joints, with a 25 mm overlap, provide higher strength than single Spot Welds (1RSW).
 

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Adhesively bonded joints, particularly those featuring Carbon Fiber Reinforced Polymer (CFRP) adherends, have become indispensable in aerospace and automotive industries due to their superior strength-to-weight ratios. However, the long-term structural integrity of these joints is severely challenged by hygrothermal environments (the synergistic effect of moisture and temperature) which induces degradation in both the polymer matrix and the adhesive interface. This review provides a systematic discourse on the fundamental principles of composites, nanotechnology, and the mechanisms of environmental aging. It critically analyzes various joint configurations and failure modes, such as cohesive and adhesive failures, under adverse conditions. A significant portion of this study is dedicated to the efficacy of incorporating zero-, one-, and two-dimensional nanoparticles to enhance the environmental resilience of epoxy adhesives. Furthermore, this review evaluates the recent advancements in Cohesive Zone Modeling (CZM) for predicting the residual strength and fracture energy of aged joints through environment-dependent traction-separation laws. This work identifies critical gaps in accelerated aging methodologies and highlights the necessity for high-fidelity predictive models to ensure the safety of hybrid structures in high-stakes engineering applications.
 

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Adhesively bonded joints, particularly the Single-Lap Joint (SLJ), are widely used in structural applications. However, stress concentrations at the overlap edges significantly limit their load-bearing capacity. Modifying the adherend geometry by introducing notches is an effective technique for stress redistribution and strength improvement. In this study, a Machine Learning (ML) approach is proposed to predict the peak peel and shear stresses in notched SLJs based on geometric parameters, namely the notch depth, notch angle, notch width, and the notch distance from the end of the overlap. First, a comprehensive dataset comprising 1183 Finite Element Analysis (FEA) simulations was generated. Subsequently, four ML models—Artificial Neural Networks (ANN), Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Machines (SVM)—were developed to map the geometric features to the maximum stress values. To ensure robust performance and prevent overfitting, a Randomized Search Cross-Validation technique was employed for hyperparameter tuning across all models prior to final evaluation. The evaluation results demonstrated highly accurate predictions across all algorithms. Specifically, the ANN model achieved the most precise results, yielding the lowest Mean Absolute Percentage Error (MAPE) for both peel (0.28%) and shear (0.16%) stresses. The SVM, XGBoost, and RF models also exhibited excellent predictive capabilities, with all MAPE values remaining well below 1%. Feature importance analysis from XGBoost and SHapley Additive exPlanations (SHAP) applied to the optimal ANN revealed that notch distance from the edge and notch depth are the key design parameters influencing stress distributions.