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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 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.

Unmanned Aircraft Systems (UAS) have been growing over the past few years and will continue to grow at a faster pace in 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 challenges and is still evolving. Hence it is essential to study on how blockchain can help UAS. G-31 technical committee of SAE International responsible for electronic transactions for aerospace has published AIR 7356 [1] entitled Opportunities, Challenges and Requirements for use of Blockchain in Unmanned Aircraft Systems Operating below 400ft above ground level for Commercial Use. This paper is a teaser for AIR 7356 [1] document.

This paper presents the current state of a three-layer surface icing model for ice crystal icing risk assessment in aircraft engines, being developed jointly by Ansys and Honeywell to account for possible heat transfer from inside an engine into the flow path where ice accretion occurs. The bottom layer of the proposed model represents a thin metal sheet as a substrate surface to conductively transfer heat from an engine-internal reservoir to the ice layer. The middle layer is accretion ice with a porous structure able to hold a certain amount of liquid water. A shallow water film layer on the top receives impinged ice crystals. A mass and energy balance calculation for the film determines ice accretion rate. Water wicking and recovery is introduced to transfer liquid water between film layer and porous ice accretion layer.

Currently, the Aviation industry uses traditional methods of communication, coordination, & human interaction to give disposition to resolve any kind of nonconformance occurrences which occur during manufacturing or operation of commercial or defense products. This involves increased in-person interaction and additional travel, especially to address the nonconformance issues arising at supplier plants or airports around the globe. During Covid and post-Covid environments, human interactions for the transfer of detailed information at different & distant manufacturing plant locations has been difficult, since support engineering teams (Example: Liaison, Product Review, Quality, Supplier Quality, and Manufacturing Engineering, and/or Service Engineering) have been working remotely.

For new aircraft production, initial production typically reveals difficulty in achieving some assembly level tolerances which in turn lead to non-conformances at integration. With initial design, tooling, build plans, automation, and contracts with suppliers and partners being complete, the need arises to resolve these integration issues quickly and with minimum impact to production and cost targets. While root cause corrective action (RCCA) is a very well know process, this paper will examine some of the unique requirements and innovative solutions when addressing variation on large assemblies manufactured at various suppliers. Specifically, this paper will first review a completed airplane project (Project A) to improve fuselage circumferential and seat track joins and continue to the discussion on another application (Project B) on another aircraft type but having similar challenges.

The aerospace ecosystem is a complex system of systems comprising of many stakeholders in exchanging technical, design, development, certification, operational, and maintenance data across the different lifecycle stages of an aircraft from concept, engineering, manufacturing, operations, and maintenance to its disposal. Many standards have been developed to standardize and improve the effectiveness, efficiency, and security of the data transfer processes in the aerospace ecosystem. There are still challenges in data transfer due to the lack of standards in certain areas and lack of awareness and implementation of some standards. G-31 standards committee of SAE International has conducted a study on the available digital data standards in aircraft asset life cycle to understand the current and future landscapes of the needed digital data standards and identify gaps. This technical paper presents the study conducted by the G-31 technical committee.

During participation on EU FP7 HAIC project, Honeywell has developed methodology to detect High Altitude Ice Crystals with the Honeywell IntuVue® RDR-4000 X-band Weather Radar. The algorithm utilizes 3D weather buffer of RDR-4000 weather radar and is based on machine learning. The modified RDR-4000 Weather Radar was successfully flight tested during 2016 HAIC Validation Campaign; the technology was granted Technology Readiness Level 6 by HAIC consortium. After the end of HAIC project, the method was also evaluated with respect to newly set preliminary industry standard performance requirements1. This paper discuses technology design rationale, high level technology architecture, technology performance, and challenges associated with performance evaluation.

An IVHM Reference Model contains relations between Symptoms, Failure Modes, Troubleshooting Tests and Corrective Actions. Since it also encodes the specific vehicle variants for which these items are applicable, it can be used to create vehicle variant specific fault isolation plans for a pattern of symptoms on a specific vehicle. This paper will discuss the methodology through which a diagnostic reasoner can use a fault model, vehicle reported symptoms and vehicle configuration data to produce a vehicle fault specific troubleshooting plan. This paper will also discuss how a wide variety of Diagnostic Work Plans can be automatically created for a platform and its variants and how these plans can be adapted by Service Engineering authors to further improve their content.

It is common for an automotive OEM to produce a wide variety of automotive models related to a common platform. As such, it is important to analyze how these variants perform with relation to reliability and warranty claims relative to each other. This paper illustrates techniques that have been applied to use warranty claim information to assess the relative reliability and incident rates for DTC occurrences, component removals, and co-occurrences with other DTCs for a family of Vehicle applications. These results are then used to identify common root cause failure modes and DTCs on specific vehicle applications that perform worse than fleet averages, and components with much lower reliability than components in similar applications. The paper concludes with an assessment of how warranty information can be used to identify precursors to future failures, identify material requirements by region and to identify product improvements in either hardware, software or service procedures:

Suppliers and integrators are working with SAE’s HM-1 standards team to develop a mechanism to allow “Health Ready Components” to be integrated into larger systems to enable broader IVHM functionality (reference SAE JA6268). This paper will discuss how the design data provided by the supplier of a component/subsystem can be integrated into a vehicle reference model with emphasis on how each aspect of the model is transmitted to minimize ambiguity. The intent is to enhance support for the analytics, diagnostics and prognostics for the embedded component. In addition, we describe functionality being delegated to other system components and that provided by the supplier via syndicated web services. As a specific example, the paper will describe the JA6268 data submittal for a typical automotive turbocharger and other engine air system components to clarify the data modeling and integration processes.

Laser Based Powder Bed Fusion, a specific application of additive manufacturing, has shown promise to replace traditionally fabricated components, including castings and wrought products (and multiple-piece assemblies thereof). In this process, powder is applied, layer by layer, to a build plate, and each layer is fused by a laser to the layers below. Depending on the component, it appears that only 3-5% of the powder charged into the powder bed fusion machine is fused. Honeywell’s initial part qualification efforts have prohibited the reuse of powder. Any unfused powder that exits the dispenser (i.e., surrounds the build or is captured in the overflow) is considered used. In order for the process to be broadly applicable in an economical manner, a methodology should be developed to render the balance of the powder (up to 97% of the initial charge weight) as re-usable.

Health Ready Components are essential to unlocking the potential of Integrated Vehicle Health Management (IVHM) as it relates to real-time diagnosis and prognosis in order to achieve lower maintenance costs, greater asset availability, reliability and safety. IVHM results in reduced maintenance costs by providing more accurate fault isolation and repair guidance. IVHM results in greater asset availability, reliability and safety by recommending preventative maintenance and by identifying anomalous behavior indicative of degraded functionality prior to detection of the fault by other detection mechanisms. The cost, complexity and effectiveness of the IVHM system design, deployment and support depend, to a great extent, on the degree to which components and subsystems provide the run-time data needed by IVHM and the design time semantic data to allow IVHM to interpret those messages.

Many avionics and aircraft equipment manufacturers use DO-160 [Ref. 1] Section 22 to test their equipment for indirect effects of lightning without understanding why they are testing to specific values. Many aircraft manufacturers struggle with determining the level of indirect lightning that will be acceptable for their vehicle and what level of requirements they need to pass down to the avionics and aircraft equipment manufacturers. Organizations like SAE and RTCA, Inc. work to collect data on lightning and spend countless hours assimilating the information and developing documents to help engineers use the information. They struggle with knowing what data is pertinent and how it will be received and used by the engineering community.

Modeling and analysis of a reduced order tracking 3-phase Phase-Locked Loop (PLL) based on a combined control principle (error + disturbance) to improve PLL locking performance is presented in this work. The principle is in synthesizing a feedforward control that is added to a Stationary/Floating Frame Transformation PLL or Synchronous (Delta Q) Frame Transformation PLL. The feedforward comprises a frequency-to-voltage converter based on a phase/frequency estimation using an algebraic summation while implementing an inverse feedforward control principle relative to the part of the feedback loop seen after the summing junction. The reduced order tracking PLL is shown to desensitize the system relative to the conventional part PI controller tuning parameters and is operated to lock on either linear or nonlinear load current waveform and for arbitrary frequency/phase profile while maintaining stability by minimizing system dynamics.

This paper discusses recent improvements made by Honeywell's Condition-Based Maintenance (CBM) Center of Excellence (COE) to Mechanical Health Management (MHM) algorithms. The Honeywell approach fuses Condition Indicators (CIs) from vibration monitoring and oil debris monitoring. This paper focuses on using MHM algorithms for monitoring gas turbine engines. First an overview is given that explains the general MHM approach, and then specific examples of how the algorithms are being refined are presented. One of the improvements discussed involves how to detect a fault earlier in the fault progression, while continuing to avoid false alarms. The second improvement discussed is how to make end of life thresholds more robust: rather than relying solely on the cumulative mass of oil debris, the end of life indication is supplemented with indicators that consider the rate of debris generation.

An emerging emphasis for the design and development of vehicle condition-based maintenance (CBM) systems amplifies its use for conducting vehicle maintenance based on evidence of need. This paper presents a systems engineering approach to creating an integrated vehicle health management (IVHM) architecture which places emphasis on the system's ultimate use to meet the operational needs of the vehicle and fleet maintainer, to collect data, conduct analysis, and support the decision-making processes for the sustainment and operations of the vehicle and assets being monitored. The demand for a CBM system generally assumes that the asset being monitored is complex or that the operational use of the system demands complexity, timely response or that system failure has catastrophic results. Ground vehicles are such complex systems, which are the emphasis of this paper. Developing the system architecture of such complex systems demands a systematic approach.

The operating environment of aircraft causes accumulation and build-up of contamination on both the narrowest passages of the ECS (Environmental Control System) i.e: the heat exchangers. Accumulated contamination may lead to reduction of performance over time, and in some case to failures causing AOG (Aircraft on Ground), customer dissatisfaction and elevated repair costs. Airframers/airlines eschew fixed maintenance cleaning intervals because of the high cost of removing and cleaning these devices preferring instead to rely on on-condition maintenance. In addition, on-wing cleaning is t impractical because of installation constrains. Hence, it is desirable to have a contamination monitoring that could alert the maintenance crew in advance to prepare and minimize disruption when contamination levels exceed acceptable thresholds. Two methods are proposed to achieve this task, The effectiveness of these methods are demonstrated using analytical and computational tools.

There is a growing need for high voltage direct current (HVDC) power distribution systems in aircraft which provide low-loss distribution with low weight. Challenges associated with HVDC distribution systems include improving reliability and reducing the size and weight of key components such as electric load control units (ELCUs), or remote power controllers (RPCs) for load control and feeder protection, and primary bus switching contactors. The traditional electromechanical current interrupting devices suffer from poor reliability due to arcs generated during repeated closing and opening operations, and are generally slow in isolating a fault with potentially high let-through energy, which directly impacts system safety.

The System Architecture Virtual Integration (SAVI) program is a collaboration of industry, government, and academic organizations within the Aerospace Vehicle System Institute (AVSI) with the goal of structuring a new integration process that relies on a “single-truth” architectural framework. The SAVI approach of “Integrate, then Build” provides a modern distributed development environment which arrests the propagation of requirements errors through the development life cycle. It does so by capturing design assumptions and shared properties of the system design in an authoritative, annotated architectural model. This reference model provides a common, analyzable framework for confirming that system requirements remain complete, consistent, and correct at all levels of system decomposition. Core concepts of SAVI include extensive use of model-based system engineering tools and use of a “single-truth” reference architectural model.