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The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces.

Squeak and rattle (SAR) noise audible inside a passenger car causes the product quality perceived by the customer to deteriorate. The consequences are high warranty costs and a loss in brand reputation for the vehicle manufacturer in the long run. Therefore, SAR noise must be prevented. This research shows the application and experimental validation of a novel method to predict SAR noise on an actual vehicle interior component. The novel method is based on non-linear theories in the frequency domain. It uses the harmonic balance method in combination with the alternating frequency/time domain method to solve the governing dynamic equations. The simulation approach is part of a process for SAR noise prediction in vehicle interior development presented herein. In the first step, a state-of-the-art linear frequency-domain simulation estimates an empirical risk index for SAR noise emission. Critical spots prone to SAR noise generation are located and ranked.

Composite materials, pioneered by aerospace engineering due to their lightweight, strength, and durability properties, are increasingly adopted in the high-performance automotive sector. Besides the acknowledged composite components’ performance, enabled lightweighting is becoming even more crucial for energy efficiency, and therefore emissions along vehicle use phase from a decarbonization perspective. However, their use entails energy-intensive and polluting processes involved in raw material production, in manufacturing processes, and, in particular, in end-of-life disposal. Carbon footprint is the established indicator to assess the environmental impact of climate-changing factors on products or services. Research on different carbon footprint sources reduction is increasing, and even the European Composites Industry Association is demanding the development of specific Design for Sustainability approaches.

Despite being ubiquitous elements in aerospace structures, thin cylindrical shells’ catastrophic buckling response under axial compression has still remained an enigma. The recent advancements in theoretical and numerical studies aided in realising the role of localisation in shell buckling. However, the buckling being instantaneous made it unfeasible for the experimental observations to corroborate the numerical results. This necessitates high-fidelity shell buckling experiments using full-filed measurement techniques. Cut-outs are deliberate and inevitable geometrical imperfections in actual structures that could dictate the buckling response. Additive manufacturing makes it feasible to fabricate shells with tailored imperfections and study various conceivable designs.

The Selective Laser Melting (SLM) process is employed in high-precision layer-by-layer Additive Manufacturing (AM) on powder bed and aims to fabricate high-quality structural components. To gain a comprehensive understanding of the process and its optimization, both modeling and simulation in conjunction with extensive experimental studies along with laser calibration studies have been attempted. Multiscale and multi-physics-based simulations have the potential to bring out a new level of insight into the complex interaction of laser melting, solidification, and defect formation in the SLM parts. SLM process encompasses various physical phenomena during the formation of metal parts, starting with laser beam incidence and heat generation, heat transfer, melt/fluid flow, phase transition, and microstructure solidification. To effectively model this Multiphysics problem, it is imperative to consider different scales and compatible boundary conditions in the simulations.

The paper presents a theoretical framework for the detection and first-level preliminary identification of potential defects on aero-structure components while employing ultrasonic guided wave based structural health monitoring strategies, systems and tools. In particular, we focus our study on ground inspection using laser-Doppler scan of surface velocity field, which can also be partly reconstructed or monitored using point sensors and actuators on-board structurally integrated. Using direct wave field data, we first question the detectability of potential defects of unknown location, size, and detailed features. Defects could be manufacturing defects or variations, which may be acceptable from design and qualification standpoint; however, those may cause significant background signal artifacts in differentiating structure progressive damage or sudden failure like impact-induced damage and fracture.

Bio-composites have gained significant attention within the aerospace industry due to their potential as a sustainable solution that addresses the demand for lightweight materials with reduced environmental impact. These materials blend natural fibers sourced from renewable origins, such as plant-based fibers, with polymer matrices to fabricate composite materials that exhibit desirable mechanical properties and environmental friendliness. The aerospace sector's growing interest in bio-composites originates from those composites’ capacity to mitigate the industry's carbon footprint and decrease dependence on finite resources. This study aims to investigate the suitability of utilizing plant derived flax fabric/PLA (polylactic acid) matrix-based bio-composites in aerospace applications, as well as the recyclability potential of these composites in the circular manufacturing economy.

Selective Laser Melting (SLM) has gained widespread usage in aviation, aerospace, and die manufacturing due to its exceptional capacity for producing intricate metal components of highly complex geometries. Nevertheless, the instability inherent in the SLM process frequently results in irregularities in the quality of the fabricated components. As a result, this hinders the continuous progress and wider acceptance of SLM technology. Addressing these challenges, in-process quality control strategies during SLM operations have emerged as effective remedies for mitigating the quality inconsistencies found in the final components. This study focuses on utilizing optical emission spectroscopy and IR thermography to continuously monitor and analyze the SLM process within the powder bed, with the aim of strengthening process control and minimizing defects.

In applications demanding high performance under extreme conditions of pressure and temperature, a range of Mechanically Attached Fittings (MAFs) is offered by various Multinational Corporations (MNCs). These engineered fittings have been innovatively designed to meet the rigorous requirements of the aerospace industry, offering a cost-effective and lightweight alternative to traditional methods such as brazing, welding, or other mechanically attached tube joints. One prominent method employed for attaching these fittings to tubing is through Internal Swaging, a mechanical technique. This process involves the outward formation of rigid tubing into grooves within the fitting. One of the methods with which this intricate operation is achieved is by using a drawbolt - expander assembly within an elastomeric swaging machine.

Industries have been increasingly adopting AI based computer vision models for automated asset defect inspection. A challenging aspect within this domain is the inspection of composite assets consisting of multiple components, each of which is an object of interest for inspection, with its own structural variations, defect types and signatures. Training vision models for such an inspection process involves numerous challenges around data acquisition such as insufficient volume, inconsistent positioning, poor quality and imbalance owing to inadequate image samples of infrequently occurring defects. Approaches to augmenting the dataset through Standard Data Augmentation (SDA) methods (image transformations such as flipping, rotation, contrast adjustment, etc.) have had limited success. When dealing with images of such composite assets, it is challenging to correct the data imbalance at the component level using image transformations as they apply to all the components within an image.

Lunar tubes, natural underground structures on the Moon formed by ancient volcanic activity, offer natural protection from extreme temperatures, radiation, and micro-meteorite impacts, making them prime candidates for future lunar bases. However, the exploration of lunar tubes requires a high degree of mobility. Given the Moon's gravity, which is approximately six times weaker than Earth's, efficient navigation across rugged terrains within these lava tubes is achievable through jumping. In this work, we present the design of subsystems for a miniature hexapod rover weighing 1 kg, which can walk, jump, and stow. The walking system consists of two subsystems: one for in-plane walking, employing four single-degree-of-freedom (DOF) legs utilizing the KLANN walking mechanism, and another for directional adjustments before jumping. The latter employs a novel three-DOF mechanism employing a cable pulley mechanism to optimize space utilization.

This research focused on developing a methodology for a vehicle dynamics model of a passenger vehicle outfitted with an aftermarket Automated Driving System software package using only literature and track based results. This package consisted of Autoware.AI (Autoware ®) operating on Robot Operating System 1 (ROS™) with C++ and Python ®. Initial focus was understanding the basics of ROS and how to implement test scenarios in Python to characterize the control systems and dynamics of the vehicle. As understanding of the system continued to develop, test scenarios were adapted to better fit system characterization goals with identification of system configuration limits. Trends from on-track testing were identified and paired with first-order linear systems to simulate physical vehicle responses to given command inputs. Sub-models were developed and simulated in MATLAB ® with command inputs from on-track testing.

In order to study the tire friction characteristics under wet skid surface, the “pseudo” hydrodynamic pressure bearing effect is used to be equivalent to the hydrodynamics of water film, and an advanced Lugre tire hydroplaning dynamic model is developed by combining the arbitrary pressure distribution function. The water hydroplaning dynamic tests were carried out for 285/70R19.5 tire under wet of different water film thickness and dry conditions, and the parameters of the advanced Lugre tire dynamic model were identified. The results show that the tire water-skiing model proposed in this paper can effectively simulate the friction characteristics of tires under different water film thicknesses. Under dry conditions, 0.5mm water film and 1mm water film road conditions, the relative errors of the maximum tire friction coefficient between the tested and advanced Lugre tire model are 1.11%, 0.12% and 0.16%, respectively.

Global automobile manufacturers are increasingly adopting vehicle architecture development systems in the early stages of product development. This strategic move is aimed at rationalizing their product portfolios based on similar specifications and functions, with the overarching goal of simplifying design complexities and enabling the creation of scalable vehicles. Nevertheless, ensuring consistent performance in this dynamic context poses formidable challenges due to the wide range of design possibilities and potential variations at each development stage. This paper introduces an efficient reliability analysis process designed to identify and mitigate the distribution of Ride and Handling (R&H) performance. We employ a range of reliability analysis techniques, including Latin Hypercube Sampling and the enhanced Dimension Reduction (eDR) method, utilizing various types of models such as surrogate models and multi-body dynamics models.

Additive manufacturing is currently being investigated for the production of components aiming for near net shape. The presence of chopped glass fibers with PA6 increases the melt viscosity and also changes the coefficients of thermal expansion and increase the heat resistance. The great dimensional stability obtained with the fusion of the PA6 with the fiber results in an extremely durable material even in adverse environments for many other materials used in 3D printing. PA6 is a material oriented for users who need to make structural parts and exposed to high mechanical stresses. The impact, test tensile, and flexural results for as-built PA6 with various infill patterns, including grid, triangle, trihexagon, and cubic, are tested.

An escalating demand for improved heat dissipation from electronic components is driven by the imperative need to eliminate the accumulated heat that gradually builds up over time. In this study, a 3-D simulation was carried out to analyze the heat distribution performance of a heat sink based on PCM/NePCM. The heat sink was subjected to varying heat fluxes ranging from 3-7 kW/m2, and its performance was evaluated over time. The findings of the computational research indicate that using PCM assists in maintaining the heat sink base's temperature within lower bounds, and leads to uniform melting within the heat sink. Further, inclusion of Alumina nano particles integration in PCM enhanced the performance of heat sink. The percentage reduction in charging time of NePCM without fins (φ = 1%, 2.5% and 5%) in comparison to the Pure-PCM (φ = 0%) is 6%, 11% and 51% respectively at 6 kW/m2 input.

The safety of commercial aviation industry has come under extensive scrutiny and how the system safety process is applied. One specific system safety regulation concerns how unsafe system operating conditions are meeting regulatory requirements. Minimal regulatory guidance was available on this topic and an industry committee (American Society for Testing of Materials) decided to provide a consensus standard with input from a cross-section of airplane manufacturers, suppliers, and regulatory authorities on what is meant by an unsafe system operating condition and how compliance can be shown to the regulation(s). The committee determined that an unsafe system operating condition is when a failure condition severity increases (to hazardous or catastrophic) due to crewmember(s) inaction. For example, if a hazard has occurred it is possible the severity can increase to an unacceptable level as the crewmember(s) are not aware of the hazard.

Previously given Paper 09ATC-0232 delivered at the SAE Aerotech conference in Seattle in 2009 reports on the E6000 machine installing slug rivets with the EMR. Paper 2015-01-2491given at the SAE conference in Seattle in 2015 reports on index head rivets being installed with screw driven squeeze process. This paper reports on the screw driven squeeze process installing unheaded slug rivet which is a more complex process. We also report on improvements to the fixture automation.