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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.

In the development of electric actuators, the electric motor to drive the actuator is quite often selected from a set of available motors that have been previously used on other similar programs, or based on legacy experience, or from those that are commercially available seeming to fit for the purpose. Scheduling and budgetary constraints pose a restriction on design and development of a new electric motor specifically for the required application. Generally, these electric motors have minimal weight but deliver maximum output power because of which they tend to heat up rapidly. Such rapid heating can lead to issues such as insulation damage or weakening of the strengths of permanent magnets used in the rotors of permanent magnet induction motors. In such cases, very early in the design phase, it becomes necessary to estimate the temperature rise of the electric motor in a cost effective and rapid way so that the best suitable motor that gives minimal temperature rise is selected.

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.

A GE Aviation Systems report documents that the National Oceanic and Atmospheric Administration (NOAA) provided weather forecast data has a bias of 15 knots and a standard deviation of 13.3 knots for the 40 flights considered for the research. It also had a 0.47 bias in the temperature with a standard deviation of 0.27. The temperature errors are not as significant as the wind. There is a potential opportunity to reduce the operational cost by improving the weather forecast. The flight management system (FMS) currently uses the weather forecast, available before takeoff, to identify an optimized flight path with minimum operational costs depending on the selected speed mode. Such a flight plan could be optimum for a shorter flight because these flight path planning algorithms are very less susceptible to the accuracy of the weather forecast.

Since the early days of aviation, when an AC-type generator became a primary source of electrical power for all aircraft systems, the demand for electrical power has steadily grown. Following rapid technology and scientific advancements in the aerospace industry, the complexity and criticality of all aircraft systems have increased to the point where multiple independent and isolated electrical power sources are required. In such an environment, with two or more variable-frequency AC-type generators that can be simultaneously activated to provide electrical power to the aircraft power distribution system, a safe power transfer process becomes a major priority. This means that any two independent aircraft AC power sources with different frequencies or phase angles cannot be connected simultaneously to a common power bus.

Pitot probes and Total Air Temperature (TAT) probes are critical to aircraft performance. They are also susceptible to becoming overwhelmed and produce erroneous outputs when flying in icing conditions, especially in high altitude ice crystal situations. When the probes are overwhelmed with ice crystals, it can have significant impacts to aircraft operations. Through design and process iterations, Collins Aerospace (also known as Rosemount Aerospace™), has developed new Appendix D compliant pitot and TAT probes that are much more capable in high ice crystal content icing environments which greatly reduce the adverse risks to the aircraft and engine systems that depend on these probes.

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.

The accurate prediction of system behavior and the stress response for vibration loads depends on how well the boundary conditions, joints, interfaces, mass, and stiffness are defined. Often, in vibration analysis several assumptions would be made due to the lack of the analytical tool capabilities, the state of art Finite Element Analysis (FEA) software still cannot handle nonlinear modal analysis. This paper attempts to develop methodology to deal with the nonlinear vibration analysis using the existing Finite Element (FE) tools. Two different aspects of nonlinearities are considered, one is impact of nonlinearities at global level in terms of predicting natural frequency & mode shapes and the other aspect is consideration of nonlinearities local to the contacts, enabling prediction of realistic stresses in the vicinity of the contacts.

The RTCA SC-230 committee began working on minimum operational performance standards (MOPS) for ice crystal detection using weather radar in 2018. The resulting MOPS document will be released in 2023. This paper presents the rationale, summarizes key requirements, and discusses means of validation for an ice crystal detection function incorporated in an airborne weather radar system.

The FE analysis of complex systems with lot of intricate features and fillets modeled in detail would result in a huge FE model size making it difficult to handle. Therefore, to reduce the computation time, defeaturing of such regions are carried out as a common practice and these critical stress concentration regions can be studied using submodeling approach later based on response superimposed from the global models. This method is widely practiced and is quite easy to implement for static and harmonic analysis problems. However, there is no well documented methodology exists for submodeling in the random vibration environment. In case of Random vibration analysis, the cut boundary displacements from Power Spectral Density (PSD) analysis would result in unrealistic stresses.

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.

Structural optimization and automation have gained a significant mileage in recent past due to advent of advancements in Computer Aided Design (CAD) and Engineering tools. The conventional approach of design cycle often results in bulkier products requiring optimization activity as a dedicated task resulting in increased overall design time. This paper discusses knowledge based integrated parametric product design philosophy which is a synergistic approach inclusive of all the functions such as design, performance, stress, manufacturing, and automation to produce optimized designs meeting all the functional requirements at preliminary design stage of the product cycle itself. This involves establishing a basic standard architecture for a product family under consideration based on legacy knowledge reflecting the Design Failure Mode Effects Analysis (DFMEA), Design for Manufacturing & Assembly (DFMA) and data driven standard works.

Circular Economy (CE) is an alternative to the traditional linear economy model. It is a systematic sustainable development strategy that seeks to tackle the deleterious effects of environmental degradation and resource scarcity. It proposes different ways to reduce waste, derive energy from renewables, recover resources at the end of a products life cycle and recycle them back into the production chain thereby significantly reducing pollution. This study is a review of the rapidly increasing literature on Circular Economy and its implementation to the Air Cargo System (ACS). It first reviews the different concepts of CE and distinguishes it from the current linear model of taking resources, making goods, and discarding waste. The study then presents how the different principles of CE can be applied to the current model of Air Cargo system and suggests ways in which the present linear model can be transformed into a regenerative sustainable model.

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.

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.

Effective contrail management while ensuring operational and economic efficiencies for flight services is essential for providing services with minimal adverse environmental impact. The paper explores various aspects of contrail management applicable to different platforms such as Unmanned vehicles, Commercial airliners and Business & regional jets. The aspects unique to each platform such as flight levels of operation, fuel types, flight endurance and radius of operation have been analyzed. Expanse of 5G network is resulting in increased flight activity at flight levels not envisaged hitherto. The paper also dwells on the ramifications of the increased proliferation of different platforms at newer flight levels from the perspective of contrail management.

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.

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.