Browse Topic: Icing and ice detection
This SAE Aerospace Recommended Practice (ARP) provides recommended practices for the calibration and acceptance of icing wind tunnels to be used in testing of aircraft components and systems and for the development of simulated ice shapes. This document is not directly applicable to air-breathing propulsion test facilities configured for the purposes of engine icing tests, which are covered in AIR6189. This document also does not provide recommended practices for creating Supercooled Large Drop (SLD) or ice crystal conditions, since information on these conditions is not sufficiently mature for a recommended practice document at the time of publication of ARP5905A. Use of facilities as part of an aircraft’s ice protection Certification Plan should be reviewed and accepted by the applicable regulatory agency prior to testing. Following acceptance of a test plan, data generated in these facilities may be submitted to regulatory agencies for use in the certification of aircraft ice
This SAE Aerospace Standard (AS)/Minimum Operational Performance Specification (MOPS) specifies the minimum performance requirements of remote on-ground ice detection systems (ROGIDS). These systems are ground based. They provide information that indicates whether frozen contamination is present on aircraft surfaces. Section 1 provides information required to understand the need for the ROGIDS, ROGIDS characteristics, and tests that are defined in subsequent sections. It describes typical ROGIDS applications and operational objectives and is the basis for the performance criteria stated in Sections 3 through 5. Section 2 provides reference information, including related documents, definitions, and abbreviations. Section 3 contains general design requirements for the ROGIDS. Section 4 contains the Minimum Operational Performance Requirements for the ROGIDS, which define performance in icing conditions likely to be encountered during ground operations. Section 5 describes environmental
Ice build-up on aircraft and wind turbines can impact the safety and efficiency of their systems.
Historically, smaller Unmanned Aerial Systems (UAS), such as Class 2 RQ-1B Raven and Class 3 RQ-7Bv2 Shadow, have been restricted to not be approved to fly in icing conditions under the assumption that any ice accretion would cause an unacceptable risk of loss of the aircraft. However, interest exists in better understanding potential icing accretion on UAS to determine if less extreme icing conditions could result in only partial degradation and not total loss of the vehicle for the purpose of expanding approved flight envelopes. Icing accretion can be tested during a flight test, which is considered unacceptable due to lack of controlled conditions and risk to the UAS or in a controlled experiment, by using wind tunnel testing to evaluate a single icing condition. Cryogenic wind tunnel tests, such as those conducted at the National Aeronautical and Space Administration (NASA) Glenn Icing Research Tunnel (IRT), Cleveland, OH, as shown in figures 1 and 2, are prohibitively expensive
Ice prediction capabilities for Unmanned Aerial Systems (UAS) is of growing interest as UAS designs and applications become more diverse. This report summarizes the current state-of-the-art in modeling aircraft icing within a computational framework as well as a recent U.S. Army DEVCOM AvMC effort to evaluate ice prediction models for current use and future integration into the Computational Research and Engineering Acquisition Tools and Environments (CREATE) Air Vehicle (AV) framework. U.S. Army Combat Capabilities Development Command, Redstone Arsenal, Alabama Historically, smaller Unmanned Aerial Systems (UAS), such as Class 2 RQ-1B Raven and Class 3 RQ-7Bv2 Shadow, have been restricted to not be approved to fly in icing conditions under the assumption that any ice accretion would cause an unacceptable risk of loss of the aircraft. However, interest exists in better understanding potential icing accretion on UAS to determine if less extreme icing conditions could result in only
Brake squeal is a common phenomenon across all types of vehicles. It becomes prominent in the absence of other noise sources, as in the case of electric vehicles. Earlier simulation attempts date back to late nineties and early 2000s. Identification of unstable modes of the coupled system of brake rotor and pads, and occasionally some caliper components, was the primary goal. Simulating the rotation of the rotor along with squeezing of the pads was attempted in a multi-body dynamics tools with flexible representation of rotor and pads. Though this gave some insights into the dynamics of stopping mechanism, squeal required capturing the nonlinearities of the contact in a more rigorous sense. Also, efforts were made to capture noise from vibrations using boundary- and finite- element methods [1]. In this attempt at digitalizing a brake dynamometer, the author used a nonlinear implicit solver to mimic the dynamics and transient vibro-acoustic solver to convert transient vibrations to
In-flight icing significantly influences the design of large passenger aircraft. Relevant aspects include sizing of the main aerodynamic surfaces, provision of anti-icing systems, and setting of operational restrictions. Empennages of large passenger aircraft are particularly affected due to the small leading edge radius, and the requirement to generate considerable lift for round out and flare, following an extended period of descent often in icing conditions. This paper describes a CFD-based investigation of the effects of sweep on the aerodynamic performance of a novel forward-swept horizontal stabilizer concept in icing conditions. The concept features an unconventional forward sweep, combined with a high lift leading edge extension (LEX) located within a fuselage induced droplet shadow zone, providing passive protection from icing. In-flight ice accretion was calculated, using Ansys FENSAP-ICE, on 10°, 15° and 20° (low, intermediate, and high) sweep horizontal stabilizers, with
The paper describes the upgrade and validation of a Cartesian solver able of estimating the mass deposition of super-cooled large droplets (SLD) on aerodynamic surfaces. A decoupled approach is applied in which the air-flow field is first computed by using a RANS method and then passed to an Eulerian solver for obtaining the water-field. Both tools are based on a finite-volume (FV) approach based on locally refined Cartesian meshes and immersed boundaries. The use of semi-empirical models allow to take into account the primary effects due to splashing and bouncing of large droplets on aerodynamic surfaces. Here, we discuss the results of a numerical campaign with the aim of estimating the accuracy of two mass-deposition models on benchmarks from different experimental databases. Besides, for some cases we compare the present results with the ones obtained by using a body-conforming method.
Ice and snow accretion on aircraft surfaces imposes operational and safety challenges, severely impacting aerodynamic performance of critical aircraft structures and equipment. For optimized location-based ice sensing and integrated ‘smart’ de-icing systems of the future, microwave resonant-based planar sensors are presented for their high sensitivity and versatility in implementation and integration. Here, a conformal, planar complementary split ring resonator (CSRR) based microwave sensor is presented for robust detection of localized ice and snow accretion. The sensor has a modified thick aluminum-plate design and is coated with epoxy for greater durability. The fabricated sensor operates at a resonant frequency of 1.18 GHz and a resonant amplitude of -33 dB. Monitoring the resonant frequency response of the sensor, the freezing and thawing process of a 0.1 ml droplet of water is monitored, and a 60 MHz downshift is observed for the frozen droplet. Using an artificial snow chamber
Icing wind tunnel testing was performed as part of the Republic of Korea certification of the Light Civil Helicopter (LCH) for inadvertent flight in icing conditions. The test was aimed at the compliance demonstration of the engine and air intake with dry-media Inlet Barrier Filter (IBF) and was performed with an Arriel 2C2 engine in turbojet configuration. Testing took place at the sea level ambient pressure Large Climatic Wind Tunnel (CWT) at Rail Tec Arsenal (RTA) in Vienna, Austria, by an integrated test team comprising engineers from the Royal Netherlands Aerospace Centre (NLR), Korea Aerospace Industries (KAI), and Safran Helicopter Engines. The test matrix covered the AC29-2C Appendix C 10,000 ft icing envelope, as well as simulated ground icing conditions, considering both a clean and artificially contaminated IBF. Beyond the aforementioned certification conditions, exploratory testing was performed in conditions with Supercooled Large Droplets (SLD) and rain. The test set-up
The Current Icing Product (CIP; Bernstein et al. 2005) and Forecast Icing Product (FIP; Wolff et al. 2009) were originally developed by the United States’ National Center for Atmospheric Research (NCAR) under sponsorship of the Federal Aviation Administration (FAA) in the mid 2000’s and provide operational icing guidance to users through the NOAA Aviation Weather Center (AWC). The current operational version of FIP uses the Rapid Refresh (RAP; Benjamin et al. 2016) numerical weather prediction (NWP) model to provide hourly forecasts of Icing Probability, Icing Severity, and Supercooled Large Drop (SLD) Potential. Forecasts are provided out to 18 hours over the Contiguous United States (CONUS) at 15 flight levels between 1,000 ft and FL290, inclusive, and at a 13-km horizontal resolution. CIP provides similar hourly output on the same grid, but utilizes geostationary satellite data, ground-based radar data, Meteorological Terminal Air Reports (METARS), lightning data, and voice pilot
To support an industry wide response to an EASA proposed Special Condition regarding the threat of in-flight supercooled liquid water icing conditions at altitudes above FL300, Boeing 777 fleet data were used to estimate the frequency and severity of such icing occurrences. The data were from the calendar year 2019 and included ~ 950,000 airline revenue flights from around the world by multiple operators. The unique architecture of the Primary Ice Detection System (PIDS) on that model, in addition to robust meteorological data that was able to be correlated, afforded an opportunity to conservatively estimate the Total Water Exposure (TWE) and thus the Liquid Water Content (LWC) of the icing encounters captured at FL295 and above. This paper will outline the key methods used and present the findings.
The paper describes a tools’ suite able of analyzing numerically 3D ice-accretion problems of aeronautical interest. The methodology consists of linking different modules each of them performing a specific function inside the ice-simulation chain. It has been specifically designed from the beginning with multi-step capability in mind. Such a feature plays a key role when studying the dynamic evolution of the icing process. Indeed, the latter has the character of a multi-physic and time-dependent phenomenon which foresees a strong interaction of the air- and water fields with the wall thermodynamics. Our multi-layer approach assumes that the physical problem can be discretized by a series of pseudo-steady conditions. The simulation process starts with the automatic generation of a Cartesian three-dimensional mesh which represents the input for the immersed boundary (IB) RANS solver. Once obtained, the air-phase is used by the Eulerian tool to solve the transport of the water-phase on
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