Aircraft icing: An ongoing threat to aviation safety

Cao, Yihua; Tan, Wenyuan; Wu, Zhenlong

doi:10.1016/j.ast.2017.12.028

Cited by 415 publications

(179 citation statements)

References 58 publications

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“…Among the parameters affect aircraft icing, the cloud type (Stratiform cloud and Cumuliform cloud) determines the liquid water content and water droplet diameter distributions [28]. In the stratiform cloud, smaller droplet diameter and lower liquid water content with larger horizontal distribution area often occur.…”

Section: Problem Descriptionmentioning

confidence: 99%

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Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost

Qin

et al. 2020

Aerospace

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Aircraft icing represents a serious hazard in aviation which has caused a number of fatal accidents over the years. In addition, it can lead to substantial increase in drag and weight, thus reducing the aerodynamics performance of the airplane. The process of ice accretion on a solid surface is a complex interaction of aerodynamic and environmental variables. The complex relationship makes machine learning-based methods an attractive alternative to traditional numerical simulation-based approaches. In this study, we introduce a purely data-driven approach to find the complex pattern between different flight conditions and aircraft icing severity prediction. The supervised learning algorithm Extreme Gradient Boosting (XGBoost) is applied to establish the prediction framework which makes prediction based on any set of observations. The input flight conditions for the proposed prediction framework are liquid water content, droplet diameter and exposure time. The proposed approach is demonstrated in three cases: maximum ice thickness prediction, icing area prediction and icing severity level evaluation. Performance comparison studies and error analysis are also conducted to verify the effectiveness and performance of the proposed method. Results show that the proposed method has reasonable capability in evaluating aircraft icing severity.

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Section: Problem Descriptionmentioning

confidence: 99%

“…The input parameters for the proposed models are LWC, droplet diameter and exposure time. The corresponding outputs are the icing severity level [28], area size covered by ice and maximum ice thickness. Performance comparison studies and error analysis are conducted to verify the effectiveness and performance of the proposed method.…”

Section: Introductionmentioning

confidence: 99%

Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost

Qin

et al. 2020

Aerospace

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“…Furthermore, if at high altitudes an aircraft encounters cumuliform or stratiform clouds (formed upon humid air rising through cooler surrounding air or horizontal spreading of lifted air, respectively), the supercooled water droplets occupying these clouds attach to and freeze instantly on the wings, airfoils and propellers of the vehicle [50]. In turn, excessive vibrations and increased aerodynamic drag may occur [50], regrettably in some cases leading to fatal accidents [51]. In addition, the heat exchangers of power and chemical plants located at arid regions may face freezing risks due to the excessive cooling capacity of ambient air, inflicting damage of the finned tube bundles [45].…”

Section: Introductionmentioning

confidence: 99%

From Extremely Water-Repellent Coatings to Passive Icing Protection—Principles, Limitations and Innovative Application Aspects

Esmeryan¹

2020

Coatings

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The severe environmental conditions in winter seasons and/or cold climate regions cause many inconveniences in our routine daily-life, related to blocked road infrastructure, interrupted overhead telecommunication, internet and high-voltage power lines or cancelled flights due to excessive ice and snow accumulation. With the tremendous and nature-inspired development of physical, chemical and engineering sciences in the last few decades, novel strategies for passively combating the atmospheric and condensation icing have been put forward. The primary objective of this review is to reveal comprehensively the major physical mechanisms regulating the ice accretion on solid surfaces and summarize the most important scientific breakthroughs in the field of functional icephobic coatings. Following this framework, the present article introduces the most relevant concepts used to understand the incipiency of ice nuclei at solid surfaces and the pathways of water freezing, considers the criteria that a given material has to meet in order to be labelled as icephobic and clarifies the modus operandi of superhydrophobic (extremely water-repellent) coatings for passive icing protection. Finally, the limitations of existing superhydrophobic/icephobic materials, various possibilities for their unconventional practical applicability in cryobiology and some novel hybrid anti-icing systems are discussed in detail.

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“…When an aircraft flies in the cloud under icing conditions, its windward surfaces collect super-cooled water droplets, and ice accretion may occur [1]. Aircraft ice accretion has a significant effect on aircraft performances.…”

Section: Introductionmentioning

confidence: 99%

Study on Loose-Coupling Methods for Aircraft Thermal Anti-Icing System

et al. 2020

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To simulate aircraft thermal anti-icing systems and solve the conjugate heat transfer of air-droplet flow and solid skin, the heat and mass transfer model of the runback water on the anti-icing surface was combined with the heat conduction equation of the skin by loosely coupled methods. According to the boundary conditions used for the runback water conservation equations, two loose-coupling methods for the heat exchange between the runback water and the solid skin were developed based on surface heat flow and surface temperature, respectively. The anti-icing and ice accretion results of a NACA 0012 electro-thermal anti-icing system were obtained by the two loose-coupling methods. The heat flow-based method directly solves the thermodynamic model of the runback water without any extra assumptions, but the convergence rate is relatively slow. On the other hand, the temperature-based method achieves higher calculation speed, but the freezing point is extended to an artificial temperature range between water and ice phases. When the value of the artificial temperature range is small, the results obtained by the temperature-based method are consistent with those of the heat flow-based method, indicating that the effect of freezing point extension can be ignored for thermal anti-icing simulation. Furthermore, the solutions of the two methods are in acceptable and comparable agreement with the experimental and simulative results in the literature, confirming their feasibility and effectiveness. In addition, it is found that the ice thicknesses and ice shapes rise obviously near the runback water limits as a result of the transverse heat conduction of the solid skin.

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Aircraft icing: An ongoing threat to aviation safety

Cited by 415 publications

References 58 publications

Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost

Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost

From Extremely Water-Repellent Coatings to Passive Icing Protection—Principles, Limitations and Innovative Application Aspects

Study on Loose-Coupling Methods for Aircraft Thermal Anti-Icing System

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