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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 descent phase of GAGANYAAN (Indian Manned Space Mission) culminates with a crew module impacting at a predetermined site in Indian waters. During water impact, huge amount of loads are experienced by the astronauts. This demands an impact attenuation system which can attenuate the impact loads and reduce the acceleration experienced by astronauts to safe levels. Current state of the art impact attenuation systems use honeycomb core, which is passive, expendable, can only be used once (at touchdown impact) during the entire mission and does not account off-nominal impact loads. Active and reusable attenuation systems for crew module is still an unexplored territory. Three configurations of impact attenuators were selected for this study for the current GAGANYAAN crew module configuration, namely, hydraulic damper, hydro-pneumatic damper and airbag systems.

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.

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.

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.

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.

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.

In the architecture of an Unmanned Aerial Vehicle (UAV), a crucial component responsible for the propulsion system is the electric motor. Over the years, different types of electric motors, including Brushless Direct Current (BLDC), have supported the UAV’s propulsion system in diverse configurations. However, in the context of flux flow, the Radial Flux Permanent Magnet Motor (RFPMM) has been given more priority than the Axial Flux Permanent Magnet Motor (AFPMM) due to its sustainability in design and construction. Nevertheless, the AFPMM boasts higher speed, power density, lower weight, and greater efficiency than the RFPMM, because of its shorter flux path and the absence of end-turn winding. Therefore, this paper focuses on conducting a suitability analysis of an AFPMM as a shaft-connected propeller-mounted motor, with the intention of replacing the RFPMM in UAV applications.

The evaluation of aircraft characteristics through flight test maneuvers is fundamental to aviation safety and understanding flight attributes. This research project proposes a comprehensive methodology to detect and analyze aircraft maneuvers using full flight data, combining signal processing and machine learning techniques. Leveraging the Wavelet Transform, we unveil intricate temporal details within flight data, uncovering critical time-frequency insights essential for aviation safety. The integration of Long Short-Term Memory (LSTM) models enhances our ability to capture temporal dependencies, surpassing the capabilities of machine learning in isolation. These extracted maneuvers not only aid in safety but also find practical applications in system identification, air-data calibration, and performance analysis, significantly reducing pre-processing time for analysts.

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.

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.

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.

Large diameter, tightly toleranced fastener patterns are commonplace in aerospace structures. Satisfactory generation of these holes is often challenging and can be further complicated by difficult or obstructed access. Bespoke tooling and drill jigs are typically used in conjunction with power feed units leading to a manual, inflexible, and expensive manufacturing process. For 777X flap production, Boeing and Electroimpact collaborated to create a novel, automated solution to generate the fastener holes for the main carrier fitting attachment pattern. Existing robotic automation used for skin to substructure assembly was modified to utilize extended length (up to 635mm), bearing-supported drill bar sub-assemblies. These Long Assembly Drills (LADs) had to be easily attached and detached by one operator, interface with the existing spindle(s), supply cutting lubricant, extract swarf on demand, and include a means for automatically locating datum features.

In numerous industries such as aerospace and energy, components must perform under significant extreme environments. This imposes stringent requirements on the accuracy with which these components are manufactured and assembled. One such example is the positional tolerance of drilled holes for close clearance applications, as seen in the “EN3201:2008 Aerospace Series – Holes for metric fasteners” standard. In such applications, the drilled holes must be accurate to within ±0.1 mm. Traditionally, this required the use of Computerised Numerical Control (CNC) systems to achieve such tight tolerances. However, with the increasing popularity of robotic arms in machining applications, as well as their relatively lower cost compared to CNC systems, it becomes necessary to assess the ability of robotic arms to achieve such tolerances. This review paper discusses the sources of errors in robotic arm drilling and reviews the current techniques for improving its accuracy.

In support of developing complex systems, integrating requirements from various source standards, such as the Military Standard (MIL-STD) series and others, presents a significant challenge. This paper explores the development of Model-Based System Engineering (MBSE) Systems Modeling Language (SysML) projects that incorporate MIL-STD requirements. The study begins by defining the critical need for integrating multiple standards into MBSE projects, emphasizing the importance of adhering to MIL-STD requirements when invoked by the customer. The study further defines the limitations inherent in managing standards independently and propose a unified approach within a SysML-based framework. The research introduces a systematic methodology for mapping MIL-STD requirements and other relevant standards onto SysML constructs, ensuring traceability and consistency throughout the system development lifecycle.

Friction stir welding (FSW) is a method of welding that creates a weld trail by pressing a non-consumable rotating tool with a profiled pin on the adjacent surfaces while moving transversely along the welding direction. The method was initially used with metals and alloys, but more recently, thermoplastic polymers have also been included in its application. Investigations on FSW of thermoplastic polymers made of nylon and High-density polythene (HDPE) are presented here. Weld characteristics that are like those of the base materials are attempted to be achieved. Because of their unique nature and thermal conductivity, thermoplastics FSW differs from that of metals. The use of thermoplastic materials with conventional FSW procedures presents numerous difficulties and is currently ineffective. On the weld characteristics of nylon and HDPE, statistical methods were utilized to study the impact of temperature, rotational speed, and transverse speed.