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The number of Unmanned Aircraft Systems (UAS) has been growing over the past few years and will continue to grow at a faster pace in the near future. UAS faces many challenges in certification, airspace management, operations, supply chain, and maintenance. Blockchain, defined as a distributed ledger technology for the enterprise that features immutability, traceability, automation, data privacy, and security, can help address some of these challenges. However, blockchain also has certain drawbacks and, additionally, it is still not fully mature. Hence it is essential to study how blockchain can help UAS. This Aerospace Information Report (AIR) presents the current opportunities, challenges of UAS operating at or below 400 ft Above Ground Level (AGL) altitude for commercial use and how blockchain can help meet these challenges. It also provides requirements for developing a blockchain solution for UAS along with the need for the standardization of blockchain enabled processes.

The aerospace industry is noticing significant shift towards More Electric Aircraft (MEA). The advancement of electrical technology the systems are being transformed towards electric compared to the conventional pneumatic or hydraulic systems. This has led to an increased demand in electrical power from 150 Kilo Watts in the conventional airplane to 1 Mega Watts in More Electric Aircraft. More electric systems, call for increased electrical wiring harness to connect various systems in the aircraft. These harnesses consist of power and data cables. Wireless communication technology is being matured for data communication, leading to reduction of wire harness for data. As of now, the length of wires in large commercial aircraft is over 100miles and it may not be surprising if the electrification of aircraft drive this too much longer.

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.

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.

Large-scale aerostructures are commonly constructed using multiple layers of stacked material which are fastened together using mechanical methods. Ensuring the interface gaps between these materials are kept within engineering tolerances is of utmost importance to the structural integrity of the aircraft over its service life. Manual, right angle feeler gauges are the traditional method for measurement of interface gaps, but this method is tedious and mechanic dependent. A portable hand tool utilizing low-coherence interferometry has been developed to address these issues. The tool uses a right-angle probe tip which is inserted into a previously drilled hole and driven through the depth of the material. A line scan of data is collected and analyzed for the presence of interface gaps. To measure the consistency of the gap around the circumference of the hole, the tool is rotated by the operator and additional scans are collected.

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.

Airborne compression-ignition engine operations differ significantly from those in ground vehicles, both in mission requirements and in operating conditions. Unique challenges exist in the aviation space, and electrification technologies originally developed for ground applications may be leveraged to address these considerations. One such technology, electrically assisted turbochargers (EATs), have the potential to address the following: increase the maximum system power output, directly control intake manifold air pressure, and reignite the engine at altitude conditions in the event of an engine flame-out. Sea-level experiments were carried out on a two-liter, four-cylinder compression-ignition engine with a commercial-off-the-shelf EAT that replaced the original turbocharger. The objective of these experiments was to demonstrate the technology, assess the performance, and evaluate control methods at sea level prior to altitude experimentation.

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.

The aircraft lifecycle involves thousands of transactions and an enormous amount of data being exchanged across the stakeholders in the aircraft ecosystem. This data pertains to various aircraft life cycle stages such as design, manufacturing, certification, operations, maintenance, and disposal of the aircraft. All participants in the aerospace ecosystem want to leverage the data to deliver insight and add value to their customers through existing and new services while protecting their own intellectual property. The exchange of data between stakeholders in the ecosystem is involved and growing exponentially. This necessitates the need for standards on data interoperability to support efficient maintenance, logistics, operations, and design improvements for both commercial and military aircraft ecosystems. A digital thread defines an approach and a system which connects the data flows and represents a holistic view of an asset data across its 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.

This technical paper reports the development of an automatic defect detector utilizing deep learning for “polished skins”. Materials with a “polished skin” are used in the fabrication of the external plates of commercial airplanes. The polished skin is obtained by polishing the surface of an aluminum clad material, and they are visually inspected, which places a significant burden on inspectors to find minute defects on relatively large pieces of material. Automated inspection of these skins is made more difficult because the material has a mirror finished surface. Defects are broadly classified into three categories: dents, bumps, and discolorations. Therefore, a defect detector must be able to detect these types of defects and measure the defects’ surface profile. This technical paper presents details related to the design and manufacture of an inexpensive automated defect detector that demonstrates a sufficiently high level of performance.

Additive manufacturing (AM) is currently the most sought-after production process for any complex shaped geometries commonly encountered in Aerospace Industries. Although, several technologies of AM do exits, the most popular one is the Direct Metal Laser Sintering (DMLS) owing to its high versatility in terms of precision of geometries of components and guarantee of highest levels of reduction in production time. Further, metallic component of any complex shape such as Gas Turbine Blades can also be developed by this technique. In the light of the above, the present work focuses on development of iron silicon carbide (Fe-SiC) complex part for ball screw assembly using DMLS technique. The optimized process parameters, hardness and wear resistance of the developed iron-SiC composite will be reported. Further, since the material chosen is a metallic composite one, the effect of SiC on the thermal stresses generated during the DMLS processing of Fe-SiC composite will also be discussed.

Robotic arms are widely known to fall short in achieving the tolerances required when it comes to the metal machining industry, especially for the aerospace sector. Broadly speaking, two of the main reasons for that are a lack of stiffness and a lack of accuracy. Robotic arm manufacturers have responded to the lack of stiffness challenge by producing bigger robots, capable of holding high payloads (e.g., Fanuc M-2000iA/2300) or symmetric robots (e.g., ABB IRB6660). Previous research proved that depending on the application and the material being machined, lack of stiffness will still be an issue, even for structurally bigger robotic arms, due to their serial nature. The accuracy issue has been addressed to a certain extent by using secondary encoders on the robotic arm joints. The encoder enhanced robotic arm solutions tend to be expensive and prior knowledge proves that there are still limitations when it comes to achieved accuracy.

The aerospace industry's unceasing quest for lightweight materials with exceptional mechanical properties has led to groundbreaking advancements in material technology. Historically, aluminum alloys and their composites have held the throne in aerospace applications owing to their remarkable strength-to-weight ratio. However, recent developments have catapulted magnesium and its alloys into the spotlight. Magnesium possesses two-thirds of aluminum's density, making it a tantalizing option for applications with regard to weight-sensitive aerospace components. To further enhance magnesium's mechanical properties, researchers have delved into the realm of metal matrix composites (MMCs), using reinforcements such as Alumina, Silicon carbide, Boron carbide and Titanium carbide.

In this work, an investigation of the enthalpy effects on the thermochemical non-equilibrium in hypersonic nozzles is performed. Three different nozzles, with different geometries and stagnation enthalpy conditions are used in this study. The three cases, two of them with stagnation enthalpy conditions of 3.3 MJ/kg and 7.56 MJ/kg, use molecular nitrogen as the testing fluid and in the third case, corresponding to the higher enthalpy condition of 23.8 MJ/kg, the fluid is partially dissociated air composed by five neutral species (N2, O2, NO, N and O). A reliable numerical model, previously validated by the authors, using non-equilibrium Navier-Stokes-Fourier equations within a density-based algorithm is here employed in the OpenFOAM framework. After an estimation of the discretization uncertainties by using the Richardson extrapolation method and Roache’s Grid Convergence Index, the results are obtained by using a sufficient independent grid for each case.

In the aerospace industry, large aircrafts employ composite materials for making complex structures which not only reduces weight and cost but also reduces the number of joints. Irrespective of that joining of structures cannot be avoided and for that mechanical fasteners such as rivets and bolts are employed along with adhesive bonding. Further, in recent years natural fibers have been studied extensively for their numerous advantages and have already been made into several automotive applications. Keeping these current trends in mind an attempt is made to investigate the joining behavior of natural fiber composites experimentally. So in this study, the ultimate failure load, bearing strength and the dominating failure mode of jute-hemp fabric-reinforced polymeric composites joined using single and double-bolted configurations are studied.

A case study of an application of Shape optimization techniques in the design of a mass simulator has been presented. A simple mass Simulator is to be designed as a replacement for a Telescope Baffle Mass for testing purposes. The simulator is made of simple plate structures like flat plates and cylindrical plates joined together. The overall mass, location of center of gravity and first few modes of the simulator need to be close to the Telescope Baffle, it is replacing. This ensures that the Simulator is a good replacement for the Telescope Baffle both in statics and dynamics performance. Shape Optimization techniques using approximate direct linearization method of MSC/Nastran software have been used to fine-tune the baseline Simulator design to achieve target properties of mass, cg, frequencies, etc.

The global electric and hybrid aircraft market utilizing lithium-ion Energy Storage Systems (ESS) as a means of propulsion, is experiencing a period of extraordinary growth. We are witnessing the development of some of the most cutting-edge technology, and with that, some of the most complex challenges that we as an industry have ever faced. The primary challenge, and the most critical cause of concern, is a phenomenon known as a “Thermal Runaway”, in which the lithium-ion cell enters an uncontrollable, self-heating state, that if not contained, can propagate into a catastrophic fire in the aircraft. A Thermal Runaway (TR) can be caused by internal defects, damage, and/or abuse caused by an exceedance of its operational specifications, and it is a chemical reaction that cannot be stopped once the cell has reached its trigger temperature.

Abstract Testing and verifying the security of connected and autonomous vehicles (CAVs) under cyber-physical attacks is a critical challenge for ensuring their safety and reliability. Proposed in this article is a novel testing framework based on a model of computation that generates scenarios and attacks in a closed-loop manner, while measuring the safety of the unit under testing (UUT), using a verification vector. The framework was applied for testing the performance of two cooperative adaptive cruise control (CACC) controllers under false data injection (FDI) attacks. Serving as the baseline controller is one of a traditional design, while the proposed controller uses a resilient design that combines a model and learning-based algorithm to detect and mitigate FDI attacks in real-time.