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Aircraft systems have a stringent requirement governed by the certifying authorities demanding that the system and components are qualified for all the applicable requirements. Conducting qualification tests on all the components in a system for all operational requirements, environmental loads, and the loads for uncertainties such as limit and ultimate cases would consume a significant time in the product design cycle. With improved computational power and with validated higher fidelity models, structural analysis is proving to be a way forward in reducing the product design cycle time. This paper discusses about the structural analysis driven qualification test definition aligning with modes of compliances defined by CS25 / FAR 25 with an objective to minimize and simplify the tests carried out as a step towards certification by analysis.

This paper provides an overview of the state-of-art multiscale “Icing Simulation Framework” capability developed at Raytheon Technologies Research Center. Specifically, the application of this framework to simulate droplet runback and runback icing will be presented. In summary, this high-fidelity framework tracks the physical mechanisms associated with droplet dynamics, ice nucleation, growth and interaction with the environment (e.g. adhesion, crystal growth, evaporation, sublimation, etc.) across all relevant scales (including nucleation at <10-7m to ~10-6m of coating/environment interaction to 10-2m of the component) which allows a rigorous investigation of how different environmental (e.g. LWC, MVD, pressure, velocity and temperature) and substrate (e.g. coating molecular and macroscopic specifications) characteristics affect the icing behavior.

For nearly a century, ice build-up on aircraft surfaces has presented a safety concern for the aviation industry. Pilot observations of visible moisture and temperature has been used a primary means to detect conditions conducive to ice accretion on aircraft critical surfaces. To help relieve flight crew workload and improve aircraft safety, various ice detection systems have been developed. Some ice detection systems have been successfully certified as the primary means of detecting ice, negating the need for the flight crew to actively monitor for icing conditions. To achieve certification as a Primary ice detection system requires detailed substantiation of ice detector performance over the full range of icing conditions and aircraft flight conditions. Some notable events in the aviation industry have highlighted certain areas of the icing envelope that require special attention.

The Collins Aerospace Optical Ice Detector is a short-range polarimetric cloud lidar designed to detect and discriminate among all types of icing conditions with the use of a single sensor. Recent flight tests of the Optical Ice Detector (OID) aboard a fully instrumented atmospheric research aircraft have allowed comparisons of measurements made by the OID with those of standard cloud research probes. The tests included some icing conditions appropriate to the most recent updates to the icing regulations. Cloud detection, discrimination of mixed phase, and quantification of cloud liquid water content for a cloud within the realm of Appendix C were all demonstrated. The duration of the tests (eight hours total) has allowed the compilation of data from the OID and cloud probes for a more comprehensive comparison. The OID measurements and those of the research probes agree favorably given the uncertainties inherent in these instruments.

In response to safety regulations regarding aircraft icing, Collins Aerospace has developed and tested a new generation of optical ice detectors (OID Lite) intended to discriminate among icing conditions described by Appendix C and Appendix O of 14 CFR Part 25 and Appendix D of Part 33. The OID Lite is a flush-mounted, short-range, polarimetric optical sensor that samples the airstream up to two meters beyond the skin of the aircraft. The intensity and polarization of the backscatter light correlate with bulk properties of the cloud, such as cloud density and phase. Drizzle-sized droplets, mixed within a small droplet cloud, appear as scintillation spikes in the lidar signal when it is processed pulse-by-pulse. Scintillation in the backscatter (in combination with the outside air temperature monitored by another probe) signals the presence of supercooled large droplets (SLD) within the cloud—a capability incorporated into the OID Lite to meet the requirements of Appendix O.

This work presents the anti-icing simulation results from a pressure sensing probe. This study used various turbulence models to understand their influence in surface temperature prediction. A fully turbulence model and a transition turbulence model are considered in this work. Both dry air and icing conditions are considered for this study. The results show that at low Angle of Attack (AOA) both turbulence model results compared well and at higher AOA the results deviated. Overall, as AOA increases, the k-ꞷ SST model predicted the surface temperature colder than the Transition SST model result.

With the publication of SAE AS5562 in 2015, icing wind tunnel test facilities have upgraded their operating environments and instrumentation to meet the client demand to test to this new standard. Nearing four years of testing and development to this standard, numerous questions and challenges have arisen that industry has addressed on an individual basis but not in a common format for all. This paper addresses some of the known challenges in an effort to apply AS5562 consistently across industry and provide clarity to all users.

The purpose of this paper to is to review the methodology applied by Collins Aerospace to develop, test and qualify a more robust surface ply rubber compound that has demonstrable improvements in durability and performance at sub-freezing temperatures. Using in-service products as a reference, pneumatic deicers in use on regional turboprop applications were selected as a basis for operational characteristics and observed failure modes. Custom test campaigns were developed by Collins to comparatively evaluate key characteristics of the surface ply material including low temperature elasticity, erosion durability, and fluid susceptibility. Collins’ proprietary engineered rubber formulations were individually evaluated and built into fully functional test deicers for component level testing to DO-160G environmental exposure, comparative ice shed performance in Collins’ Icing Wind Tunnel and erosion in Collins’ Rain Erosion Silo.

Wind tunnel facilities typically rely upon reference instrumentation combined with isentropic flow relationships to define the fluid properties in the test section. For the particular case of icing wind tunnels, the icing environment can affect the airflow such that the definition of test section parameters via isentropic relationships is not strictly correct. These influences are of particular importance for testing air data probes because the nature of the test is to evaluate the performance of a sensor directly measuring the parameters being affected. Momentum, heat, and mass transfer from the water phase to the air phase can result in total temperature and total pressure measurements in the test section that differ from those measured at an upstream station, where reference measurements are typically taken. This effect was first observed by Luers & Fiscus [1] in the context of wind tunnel tests for heavy rain conditions.

In response to new safety regulations regarding aircraft icing, Collins Aerospace has developed and tested an Optical Ice Detector (OID) capable of discriminating among icing conditions appropriate to Appendix C and Appendix O of 14 CFR Part 25 and Appendix D of Part 33. The OID is a short-range, polarimetric lidar that samples the airstream up to ten meters beyond the skin of the aircraft. The intensity and extinction of the backscatter light correlate with bulk properties of the cloud, such as water content and phase. Backscatter scintillation (combined with the outside air temperature from another probe) signals the presence of supercooled large droplets (SLD) within the cloud-a capability incorporated into the OID to meet the requirements of Appendix O. Recent laboratory and flight tests of the Optical Ice Detector have confirmed the efficacy of the OID to discriminate among the various icing conditions.

Since the beginning of aviation, aircraft designers, researchers, and pilots have monitored the skies looking for clouds to determine when and where to fly as well as when to deice aircraft surfaces. Seeing a cloud has generally consisted of looking for a white / grey puffy orb floating in the sky, indicating the presence of moisture. A simple monitoring of a temperature gauge or dew point sensor was used to help determine if precipitation was likely or accumulation of ice / snow on the airframe could occur. Various instruments have been introduced over the years to identify the presence of clouds and characterize them for the purposes of air traffic control weather awareness, icing flight test measurements, and production aircraft ice detection. These instruments have included oil slides, illuminated rods, vibrating probes, hot wires, LIDAR, RADAR, and several other measurement techniques.

The aircraft jet engine is one of the most complex multivariable systems with multiple inputs and multiple outputs. To attempt to optimize control functions or to address diagnostic problems, a detailed knowledge of all jet engine design parameters and performances is required. Although jet engines have been around for almost a century, there are only a few companies in the world presently designing and manufacturing them; as such these companies possess detailed knowledge of all relevant design characteristics and performance parameters. In the event where jet engine technical details are unknown, or only a few of them are known from manufacturer’s catalogues, the challenge becomes how to calculate and extrapolate critical performance parameters based on only fuel flow, jet exhaust temperature and total thrust.

Protecting against atmospheric icing conditions is critical for the safety of aircraft during flight. Sensors and probes are often used to indicate the presence of icing conditions, enabling the aircraft to exit the icing cloud and engage their ice protection systems. Supercooled large drop (SLD) icing conditions, which are defined in Appendix O of 14 CFR Part 25, pose additional risk to aircraft safety as compared to conventional icing conditions, which are defined in Appendix C of 14 CFR Part 25. For this reason, developing sensors that can not only indicate the presence of ice, but can also differentiate between Appendix O (App O) and Appendix C (App C) icing conditions, is of particular interest to the aviation industry and to federal agencies. Developing a detector capable of meeting this challenge is the focus of SENS4ICE, a European Union sponsored project.

The aircraft asset life cycle processes are rapidly being digitalized. Many novel technologies enabled processes of recording these electronic transactions are being emerged. One such technology for recording electronic transactions securely is Blockchain, defined as distributed ledger technologies which includes enterprise blockchain. Blockchain is not widely used in the aerospace industry due to lack of technical understanding and questions about its benefits. Assessment and establishment of business case for implementing blockchain based solution is needed. The aerospace industry is very conservative when it comes to technology adoption and hence it is difficult to change legacy processes. Additionally, the industry is very fragmented. The technology is advancing at a faster rate and applies across geographies under various regulatory oversight which makes blockchain based solution implementation challenging.

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.

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.

Innovative carbon nanotube (CNT) electrothermal heating technology for ice protection systems is one of the alternatives under development that shall contribute to more efficient and sustainable aircraft. CNT heater technology allows for more rapid heat up rates over legacy metallic electrothermal heaters that utilize resistance wires or metallic foils. This more rapid heat up rate can lead to more energy efficient electrothermal ice protection system designs and is being studied to determine how much the rapid heat up properties of CNT can lead to a minimization of residual ice build-up aft of the heated area. Due to the inherent redundancy of CNT material used, leads to a very robust and damage tolerant heating element. To mature this technology to prepare to implement CNT on an in-service aircraft platform, a multi-staged flight testing effort to prove out the technology on an actual aircraft and in a relevant environment is mandatory.

Avionics systems are currently undergoing a transition from single core processor architectures to multi-core processor architectures. This transition enables significant advantages in reduction in size, weight, power (SWaP) and cost. However, avionics hardware and software certification policies and guidance are evolving as research and experience is gained with multi-core processor architectures. The unique challenges of using multi-core processors in certified avionics will be discussed. The requirements for a virtualization platform supporting multiple real-time operating system (RTOS) partitions on a multi-core processor used in safety-critical avionics systems are defined, including the ability to support multiple design assurance levels (DAL) on multiple cores, fault isolation and containment, static configuration as per ARINC 653, role-based development as per DO-297, and robust partitioning to reduce cost of incremental certification.

Electric aircraft have emerged as a promising solution for sustainable aviation, aiming to reduce greenhouse gas emissions and noise pollution. Efficiently estimating and optimizing energy consumption in these aircraft is crucial for enhancing their design, operation, and overall performance. This paper presents a novel framework for analyzing and modeling energy consumption patterns in lightweight electric aircraft. A mathematical model is developed, encompassing key factors such as aircraft weight, velocity, wing area, air density, coefficient of drag, and battery efficiency. This model estimates the total energy consumption during steady-level flight, considering the power requirements for propulsion, electrical systems, and auxiliary loads. The model serves as the foundation for analyzing energy consumption patterns and optimizing the performance of lightweight electric aircraft.

Protecting against atmospheric icing conditions is critical for the safety of aircraft during flight. Sensors and probes are often used to indicate the presence of icing conditions, enabling the aircraft to engage their ice protection systems and exit the icing cloud. Supercooled large drop icing conditions, which are defined in Appendix O of 14 CFR Part 25, pose additional aircraft certification challenges and requirements as compared to conventional icing conditions, which are defined in Appendix C of 14 CFR Part 25. For this reason, developing sensors that can not only indicate the presence of ice, but can also differentiate between Appendix O and Appendix C icing conditions, is of particular interest to the aviation industry and to federal agencies. Developing detectors capable of meeting this challenge is the focus of SENS4ICE, a European Union sponsored project.