Browse Topic: Icing and ice detection
This study investigates the phenomenon of receptacle icing during Compressed Natural Gas (CNG) refueling at filling stations, attributing the issue to excessive moisture content in the gas. The research examines the underlying causes, including the Joule-Thomson effect, filter geometries, and their collective impact on flow interruptions. A comprehensive test methodology is proposed to simulate real-world conditions, evaluating various filter types, seal materials and moisture levels to understand their influence on icing and flow cessation. The findings aim to offer ideas for reducing icing problems. This will improve the reliability and safety of CNG refueling systems.
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
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 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
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.
A fundamental understanding of the icing process for aircraft requires a more thorough analysis of the thermodynamics of supercooled droplet impingement. To better study such thermodynamic processes, a novel temperature sensor that functions within supercooled water and ice crystals was developed. The temperature sensor is non-intrusive and provides temperature and phase change information for both liquid water and solid ice. The temperature sensor is an optical sensor based on the luminophore pyranine. The use of pyranine allows for the measurement of spatially and temporally resolved temperature fields for icing applications. The sensitivity of the sensor is -9.2±0.1%/K for temperature measurement in the solid phase and 0.8±0.1%/K for the liquid phase. The performance of the sensor was demonstrated through a calibration process using spectral analysis, the observation of the melting process of a rectangular prism created from the luminescent ice, and the study of the temperature
Modeling of icing is important for the design of aircraft lifting surfaces and for the design of efficient propulsion systems. The computational modeling of ice accretion prediction is important to replace the expensive experimental techniques for calculating the ice shapes in Icing tunnels, and the first step toward modeling ice accretion is to accurately compute the droplet collection efficiency which acts as the input to the accretion model. In this work, we perform large-eddy simulations of supercooled droplet transport and impingement onto complex aircraft geometries using a Lagrangian particle approach. We assess the improvement in modeling droplet impingement by computing the droplet collection efficiency and by comparing with the existing experimental data.
Considerable amounts of water accumulate in aircraft fuel tanks due to condensation of vapor during flight or directly during fueling with contaminated kerosene. This can result in a misreading of the fuel meters. In certain aircraft types, ice blocks resulting from the low temperatures at high altitude flights or in winter time can even interfere with the nozzles of the fuel supply pipes from the tanks to the engines. Therefore, as part of the maintenance operations, water has to be drained in certain intervals ensuring that no remaining ice is present. In the absence of an established method for determining residual ice blocks inside, the aircraft operator has to wait long enough, in some cases too long, to start the draining procedure, leading potentially to an unnecessary long ground time. A promising technology to determine melting ice uses acoustic signals generated and emitted during ice melting. With acoustic emissions, mainly situated in the ultrasonic frequency range, a very
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.
The numerical simulation of ice accretion on aircraft is a complex problem that is difficult to simulate robustly, especially in 3D. The process, which combines multiple different solvers, is prone to fail whenever the geometry deformation due to ice is too complex. Thus, the more ice layers, the more fragile is the simulation. This paper aims at studying, and possibly reducing, the dependency on the number of layers by considering i) the impact of the deforming surface on the impingement and ii) a local roughness modeling that can better position the ice horns. The method called Impact Angle Correction (IAC) method in the literature is implemented and consists in setting in an additional loop the components solved on the surface, namely the thermodynamic exchanges and the geometry update, to consider the change in the surface normal vectors. For each of these ice sub-layers, the impingement water mass is recomputed by considering all droplet bins after each deformation of the surface
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
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