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Abstract Crash simulation is targeted mainly carried out by the collision regulations FMVSS simulation to identify problems in vehicle structures. A modern car structure consist of several thousand weld-type connections, and failure in these connections plays an important role for the crashworthiness of the vehicle. Therefore accurate modeling of these connections is important for the automotive industry in order to improve Vehicle collision characteristics. In pursuit of this key requirement, we introduced a proper methodology for the development detailed weld model to study structural response of the weld when the applied load range is beyond the yield strength. Three-dimensional finite element (FE) models of spot welded joints are developed using the LS-Dyna FE code. In this process the force estimation model of spot welds is explained. The results from this paper shows good agreement between the simulations and the tests.

Abstract The main aim of this study is to understand the effect of thermal conditions on the fatigue resistance of one automotive Daytime Running Lamp (DRL) housing made of Polycarbonate (PC) material. Automotive lighting products are made of mostly thermoplastic materials. Thermoplastic materials have mechanical properties varying significantly by temperature. As a result, thermal conditions at service life must be considered before evaluating the mechanical performance of automotive lighting products. In this study, thermal finite element analysis (FEA) has been done in order to understand the temperature distribution on DRL components at different thermal environments. Thermal map files representing the temperature distributions of the DRL components have been extracted and entered as load inputs into the modal FEA to find out the resonance frequencies. Using material properties varying by temperature, resonance frequencies of the DRL have been found by modal analysis and compared.

Abstract Welding is a dominant joining process employed in fabrication industries, especially in critical areas such as boiler, pressure vessels, and marine structure manufacturing. Online monitoring of welding processes using sensors and intelligent models is increasingly used in industries for predicting weld conditions. Studies are conducted in a Shielded Metal Arc Welding (SMAW) process using sound, current, and voltage sensors to predict the weld conditions. Sensor signatures are acquired from the good weld and defective weld conditions established in this study. Signal processing is carried out, and time-domain statistical features are extracted. Statistical features are also extracted from the power waveform derived from the current and voltage data for all the weld conditions. Classification And Regression Tree (CART) and Support Vector Machine (SVM) algorithms are used to build the statistical models to predict the weld conditions.

Abstract Aluminum boron carbide (Al-B4C) composites have been a popular choice among scientists and designers for high-performance strength-to-weight ratio engineering applications. Requirements for such applications are met due to enhanced microstructure, mechanical properties, and ease of processing conditions. The performance and application of these composites are mostly dependent on certain parameters, like composition ratios of reinforcing particles, their sizes and wettability, the presence of additional phases, etc. Prominently, efforts are also being made to synthesize Al-B4C as functionally graded materials (FGMs) that have the potential to cater to the needs of advanced engineering applications and can facilitate new dimensions in the field of aluminum matrix composites (AMCs).

Abstract The impact of Laser Beam Machining (LBM) process parameters on Surface Roughness (SR) and kerf width during machining is investigated in this work. Stainless Steel is a material that is resistant to corrosion. LBM is a nontraditional machining method in which material is removed by melting and vaporizing metal when a laser beam collides with the metal surface. There are numerous process variables that influence the quality of the LBM-cut machined surface. However, the most essential factors are laser power, cutting speed, assist gas pressure, nozzle distance, focus length, pulse frequency, and pulse width. SR, Material Removal Rate (MRR), and kerf width and heat affected zone are significant performance indicators in LBM. The influence of LBM process parameters on SR and kerf width while machining stainless steel material is investigated in this study.

Abstract This work presents an experimental analysis of the bulk content characterization of 2024 T351 Aluminum alloy under cyclic loadings used for precision applications such as balancing, optical, and laser instruments. Test samples with various machining directions (longitudinal and orthogonal) are formed using a CNC milling machine. Inelastic and plastic deformations in the nanoscale are the investigated characteristics of interest; hence, the fabric’s time constant at a fixed quarter-hour span. Samples with specific geometry are subjected to a tensile stress range of 10-150 N/mm2 provided by an electromagnetic test device. It should be said that all types of deformations considered were measured with and without loading using interferometers and capacitive sensors. Experiments are performed under constant temperature-stable housing whereas experimental measurements are recorded within the residual strain range of 10 microns.

Abstract Aircraft lift bag is the equipment used for the recovery of an aircraft and is considered as a lifting equipment. Boeing 737 is a domestic aircraft considered for designing this bag. The aircraft lift bag is made of composite material, and the most widely used materials are nylon and neoprene. A composite material is used to make the bag lightweight and easy to handle. For calculation of properties and the engineering constant of the respective composite materials, micromechanics approach is used, in which the method of Representative Volume Element (RVE) is taken into consideration. The loading and boundary conditions are the exact replica of the working conditions. The operation of this bag is completely pneumatic. The stresses induced in the bag are analyzed in finite element software and are compared with the calculated theoretical values. CATIA is used to model the bag, and ABAQUS is used for the finite element calculations.

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Abstract Knurling joint applied in assembled camshaft has developed rapidly in recent years, which have exhibited great advantages against conventional joint methods in the aspects of automation, joint precision, thermal damage, noise, and near net shape forming. Both quality of assembly process and joint strength are the key requirements for manufacturing a reliable assembled camshaft. In this article, a finite element predictive approach including three subsequent models (knurling, press-fit and torsion strength) has been established. Johnson-Cook material model has been used to simulate the severe plastic deformation of the material. The residual stress field calculated from the knurling process was transferred as initial condition to the press-fit model to predict the press-fit load. The predicted press-fit load, torque strength and displacement of cam profile before failure were calculated.

Abstract The increasing use of aluminum alloy extrusion in automotive vehicle chassis as structural members has necessitated the need to investigate their crushing behaviors. This article experimentally examines in detail, for the first time with respect to strength, ductility, and microstructure, AA6063-T7 (overaged) condition and the standard T6 temper and their capacity to meet crashworthiness requirements. Both tempers were assessed based on their mechanical properties (strength, ductility, true stress/strain behavior to necking, plastic anisotropy, strain rate sensitivity, and post-instability ductility to fracture) and microstructure, which were determined using basic tensile testing methods and metallographic approach.

Lightweighting in the automotive industry has been primarily motivated by fuel economy and greenhouse gas emission targets. The target greenhouse gas emissions and, therefore, the fuel economy for the average vehicle in both the United States and European Union are required to achieve significant annual improvements through 2026. Weight reduction, or lightweighting of an automobile, provides improvements not only in the fuel economy of engine-powered vehicles but also provides for improvements in the driving range of electric vehicles. As an industry example, the 2017 Chrysler Pacifica minivan utilizes a blend of high-strength steels, aluminum, and magnesium to reduce vehicle weight by over 100 kg, helping achieve a nearly 10% reduction in greenhouse gas emissions in a larger vehicle footprint with increasing industry safety demands [1].

Abstract Heavy commercial vehicles play an important role in creating the trade and economic balance of countries. Also, the durability and safety of heavy commercial vehicles come to the fore. Heavy commercial vehicles consist of two parts. These are the chassis area with the equipment that allows the vehicle to move and the cabin section where the driver is located. The cabin area is the most important area that ensures the highest level of driver safety. Considering that the production of trucks is increasing day by day, it is inevitable for companies to increase their R&D activities in the field of cabin and cabin suspension systems for much safer, durable, and comfortable trucks. This study aims to determine the safe torque value of the fasteners and their assembly sequence of the Cab Suspension Console, which is one of the most important connection parts in a truck and which can cause a fatal accident by breaking.

Abstract In this article, Al-Mg-Si-Mn alloy (AA6082) is butt joined by employing friction stir welding (FSW). The mechanical and metallurgical properties of joints are analyzed by conducting tensile and microhardness testing, respectively. To measure the temperature at different locations, eight thermocouples (L-shaped k-type) are placed at equal distance from the centerline. Least square method attempts to calculate the temperature at the centerline of joints. The process parameters are also optimized using Taguchi’s five-level experimental design. The optimum process parameters are determined, employing ultimate tensile strength (UTS) as a response parameter. A statistical test “analysis of variance” is used to check the adequacy of the model. It has been observed that rotational speed and feed rate are the predominant factors for UTS and microhardness.

Abstract Slag, generated from basic oxygen furnace (BOF) or Linz-Donawitz (LD) converter, is one of the recyclable wastes in an integrated steel plant. The present work aims at utilization of waste LD slag to develop surface coatings by plasma spraying technique. This study reveals that LD slag can be gainfully used as a cost-effective wear-resistant coating material. A prediction model based on an artificial neural network (ANN) is also proposed to predict the erosion performance of these coatings. The 2.27% error shows that ANN successfully predicts the erosion wear rate of the coatings both within and beyond the experimental domain. In addition to it, a novel optimization algorithm called imperialist competitive algorithm (ICA) is used to obtain minimum erosion wear rate of 12.12 mg/kg.

Abstract Industry 4.0 is expected to revolutionize product development and, in particular, manufacturing systems. Cyber-physical production systems and digital twins of the product and process already provide the means to predict possible future states of the final product given the current production parameters. With the advent of further data integration coupled with the need for autonomous decision-making, methods are needed to make decisions in real time and in an environment of uncertainty in both the possible outcomes and in the stakeholders’ preferences over them. This article proposes a method of autonomous decision-making in data-intensive environments, such as a cyber-physical assembly system. Theoretical results in group decision-making and utility maximization using mixture distributions are presented. This allows us to perform calculations on expected utility accurately and efficiently through closed-form expressions, which are also provided.

Abstract Increasing the strength of materials is effective in reducing weight and boosting structural part performance, but there are cases where the residual strain generated during the process of manufacturing of high-strength materials results in a decline of durability. It is therefore important to understand how the residual strain in a manufactured component changes due to processing conditions. In the case of a connecting rod, because the strain load on the connecting rod rib sections is high, it is necessary to clearly understand the distribution of strain in the ribs. However, because residual strain is generally measured by using X-ray diffractometers or strain gauges, measurements are limited to the surface layer of the parts. Neutron beams, however, have a higher penetration depth than X-rays, allowing for strain measurement in the bulk material.

Abstract Fatigue performance can be a critical attribute for the production of structural parts or components via additive manufacturing (AM). In comparison to the static tensile behavior of AM components, there is a lack of knowledge regarding the fatigue performance. The growing market demand for AM implies the need for more accurate fatigue investigations to account for dynamically loaded applications. A357.0 parts are processed by laser-based powder bed fusion (L-PBF) in order to evaluate the effect of surface finishing on fatigue behavior. The specimens are surface finished by shot peening using ϕ = 0.2 and ϕ = 0.4 mm steel particles and ϕ = 0.21-0.3 mm zirconia-based ceramic particles.

Abstract It is clear that modern carbon fiber (CF) manufacturing methods will go beyond luxurious or limited-use CF products toward a vast and unlimited commercial revolution of CF uses in multiple engineering applications. This expansion of the unlimited use of CF will be a major challenge for researchers to provide in-depth information to define the mechanical properties of CF products and the extent to which these properties are affected by various environmental factors. Therefore, defining the carbon fiber-reinforced polymer (CFRP) properties under different loading and environmental conditions is critical for extreme operating conditions. Sunlight, heat, and humidity have become a research focus to explore the impact of these parameters on the morphological and mechanical characteristics of the CFRP.

Abstract AA7075 is susceptible to localized corrosion like exfoliation corrosion (EXCO), intergranular corrosion (IGC), and stress corrosion cracking (SCC). Its susceptibility is strongly affected by heat treatments. In this study, the effects of two heat treatments applied to AA7075 alloy at a different time and temperature on EXCO, IGC, and SCC were investigated. Furthermore, a joining corrosion evaluation using self-piercing riveting (SPR) was conducted. It was concluded that, when compared to the traditional T6 aging process, the samples subjected to a novel advanced aging process with a significantly reduced aging time were comparable with respect to the resistance to EXCO, IGC, SCC, and SPR joining corrosion.