This study presents a combined test and numerical investigation of heat transfer characteristics and anti-icing performance of a nacelle hot-air anti-icing system, which employs a double-row impinging jet configuration integrated with a piccolo tube. High-resolution Nusselt number distributions on the inner surface of the anti-icing cavity were obtained by using transient thermochromic liquid crystal thermography over a Reynolds number range of 15 000 to 40 000, leading to the establishment of a heat transfer correlation model suitable for engineering applications. Through internal-to-external conjugate heat transfer simulations, the anti-icing temperature distributions under typical nacelle operating conditions were further analyzed. The results demonstrate that increasing the Reynolds number from 15 000 to 40 000 enhances the average Nusselt number at the inner lip surface by a factor of 2.4 and raises the hot-air consumption by approximately 2.7 times, whereas the average anti-icing surface temperature increases by only 28.4 ℃. These findings indicate that merely increasing hot-air mass flow provides limited improvement in anti-icing efficiency and highlight substantial potential for reducing air consumption through structural optimization and heat transfer enhancement. Moreover, variations in the angle of attack significantly influence anti-icing performance, as a 5.6° angle of attack reduces the average surface temperature by approximate 13.6 ℃ compared to the 0° condition, underscoring the importance of optimizing jet arrangement to align with regions experiencing the highest icing loads.

A study on ice accretion characteristics of the full-size tri-element airfoil of typical large airplane was conducted using a combined approach of numerical and experimental methods. Numerical techniques specifically developed for simulations of icing on multi-element airfoil structures were implemented on the NNW-ICE software platform. These techniques include a highly efficient Lagrangian method for droplet collection, an icing simulation method featuring the unsteady flow of water film, and a reconstruction method for calculating the evolution of volume grids and ice layers in multi-shot icing simulations. Then, the full-size tri-element airfoil was utilized in simulations using the NNW-ICE software, as well as in experimental tests conducted in the 3 m × 2 m large-scale icing wind tunnel at the Chinese Aerodynamics Research and Development Center. A detailed analysis was performed on the icing characteristics of the back of the slat wing. The results indicate that ice can unexpectedly accumulate on the lower side of the flap wing and the back of the slat wing, in addition to the accumulation observed on the windward leading edge of both the slat wing and the main wing. This study revealed for the first time that the ice on the back of the slat wing exhibits a unique double-ridge ice shape, and the formation mechanism of the ice shape was interpreted through numerical analysis. The results and findings can provide valuable references for the design of high-lift and anti-/de-icing devices in the aircraft.

Ice accretion on aircraft surface degrades aircraft's aerodynamic performance and results in unpredictable disasters. Large-scale icing wind tunnels are essential for studying the growth process of the ice accretion on aircraft surfaces, the key to which is obtaining the precise ice shape. In the present paper, we developed a laser line scanning imaging-based system for online measuring the three-dimensional geometry of ice accretion in large-scale icing wind tunnels. This system has been successfully demonstrated in tests using an aircraft wing model at China Aerodynamics Research and Development Center's 3 m×2 m icing wind tunnel. Prior to scanning, a tridimensional calibration device was used to acquire all laser plane coefficients, which were later combined with camera calibration parameters to establish a mapping function between image and real-world dimensions. Using a combination of the Steger method and gradient barycenter calculation, we accurately located the laser lines on the intricate ice surface and calculated its three-dimensional coordinates, which were used to reconstruct the entire three-dimensional ice geometry. Experimental results indicate that our measurement system has a repeatability accuracy of 0.18 mm; it can effectively capture the three-dimensional geometry of rime, mixed and clear ice on the airfoil model's leading edge during the growth process. Our results agree well with commercial 3D scanners, with an overall standard deviation of 0.5 mm.

Icing simulation of a 30P30N multi-element airfoil is conducted to explore the aerodynamic characteristics influenced by ice shape on the multi-element airfoil under different inflow conditions. An improved multi-time step calculation method based on the Myers icing phase transition model is proposed. A robust and efficient Lagrangian water collection calculation is realized by introducing the minimum wall distance. The local mesh repair technique is applied to improve the robustness of mesh reconstruction under complex ice conditions. The calculation results show that the ice shape is distributed at the leading edge of the slat airfoil and the lower surface of the main element and the flap airfoil. The droplet collection on the multi-element airfoil surface has significant unsteady characteristics due to the influence of the upstream component wake. Ice accretion on the leading edge slat and ice blocking in the crack near the slat are the main factors leading to the aerodynamic performance degradation, while the ice on the flap surface has a smaller impact for the lift and drag efficiency.

A quantitative identification method for in-flight icing has the capability to significantly enhance the safety of aircraft operations. Ultrasonic guided waves have the unique advantage of detecting icing in a relatively large area, but quantitative identification of ice layers is a challenge. In this paper, a quantitative identification method of ice accumulation based on ultrasonic guided waves is proposed. Firstly, a simulation model for the wave dynamics of piezoelectric coupling in three dimensions is established to analyze the propagation characteristics of Lamb waves in a structure consisting of an aluminum plate and an ice layer. The wavelet transform method is utilized to extract the Time of Flight (ToF) or Time of Delay (ToD) of S₀/B₁ mode waves, which serves as a characteristic parameter to precisely determine and assess the level of ice accumulation. Then, an experimental system is developed to evaluate the feasibility of Lamb waves-based icing real-time detection in the presence of spray conditions. Finally, a combination of the Hampel median filter and the moving average filter is developed to analyze ToF/ToD signals. Numerical simulation results reveal a positive correlation between geometric dimensions (length, width, thickness) of the ice layer and ToF/ToD of B₁ mode waves, indicating their potential as indicators for quantifying ice accumulation. Experimental results of real-time icing detection indicate that ToF/ToD will reach greater peak values with the growth of the arbitrary-shaped ice layer until saturation to effectively predict the simulation results. This study lays a foundation for the practical application of quantitative icing detection via ultrasonic guided waves.

The efficiency of the aircraft Ice Protection Systems (IPSs) needs to be verified through icing wind tunnel tests. However, the scaling method for testing the IPSs has not been systematically established yet, and further research is needed. In the present study, a scaling method specifically designed for thermal IPSs was derived from the governing equation of thin water film. Five scaling parameters were adopted to address the heat and mass transfer involved in the thermal anti-icing process. For method validation, icing wind tunnel tests were conducted using a jet engine nacelle model equipped with a bleed air IPS. The non-dimensional surface temperature and runback ice closely matched for both the reference and scaled conditions. The validation confirms that the scaling method is capable of achieving the similarity of surface temperature and the runback ice coverage. The anti-icing scaling method can serve as an important supplement to the existing icing similarity theory.

When ships sail in cold and harsh maritime environments such as the polar regions, sea spray can easily cause their superstructure to be frozen. Severe ice accumulation can pose a threat to the safety of ship navigation and outdoor environment operations. Accurate prediction of ice accretion due to sea spray is important to ensure safe operations in polar regions. The main difference between sea spray icing and splashing pure water freezing is the effect of salinity, thus sea spray is often simplified as salty liquid water droplets. Numerical simulation is an important means to study the icing of salty liquid water. The movement and heat/mass transfer process of salty liquid water are key factors in the numerical simulation of salty droplet icing, which determine the impingement characteristics of salty droplets and the physical quantity of impacting droplet related to icing. Based on the heat transfer model SHIPICE, we have proposed a coupled model of heat and mass transfer that considers both the loss of mass and the change in salinity during the movement of salty droplets. On the NNW-ICE platform, we have developed a coupled numerical calculation method and the corresponding program for salty droplet movement and heat/mass transfer process in the Lagrange framework, which realizes the simulation of heat and mass transfer process of moving salty droplets. Key influencing factors in the salty droplet movement and heat/mass transfer process are explored, and the heat and mass transfer effects under different conditions of incoming flow velocity, temperature, relative humidity and salty droplet diameter conditions, are systematically analyzed, laying the foundation for further development of numerical calculation methods for salty droplet icing.

To achieve regionalized quantitative detection of aircraft icing, we propose a method for ice layer localization and quantitative identification based on the Lamb waves. Firstly, a wave dynamic simulation model of piezoelectric coupling is established. The propagation characteristics and mode conversion process of the Lamb waves in the aluminum plate and ice layers are analyzed with the three-dimensional finite element method. The S₀/B₁ mode is selected as the icing monitoring mode, and a signal analysis method based on wavelet transform is developed to extract the time of delay of S₀/B₁ mode waves. Furthermore, the influence of different ice layer structural sizes on the Lamb wave signals is analyzed. It is found that the time of delay ratio of the B₁ mode waves linearly increases with the increase in the ice layer length (ice accumulation in the direction of wave propagation). The ice layer width (ice accumulation in the direction perpendicular to the wave propagation) has a range of influence on the time delay of the B₁ mode waves. For the range of ice layer width not exceeding 40 mm, the time of delay ratio has a linear relationship with the width of ice. The ice layer thickness shows an approximate positive correlation with the time of delay ratio of the B₁ mode waves, and a good linear relationship exists between them within an ice layer thickness of 1.5 mm. Finally, a simulation model of the Lamb waves piezoelectric array is established, and a modified reconstruction algorithm for the probabilistic inspection is proposed. The ice accumulation level is characterized by the time of delay to verify the feasibility of ice layer localization imaging and quantitative identification in the detection area and improve the ability to rapidly evaluate icing online based on ultrasonic guided waves, laying the foundation for icing quantitative detection via ultrasonic guided waves.

The 3 m × 2 m Icing Wind Tunnel, a key national scientific and technological facility of Chinese "Eleventh Five -Year Plan", is the largest non-seasonal icing wind tunnel in the world. Since its establishment in 2013, the facility has completed more than 70 tests, which strongly supports the domestic aircraft's independent development and airworthiness certification. The composition and characteristics of the 3 m × 2 m icing wind tunnel are first introduced. Secondly, several new progress in improving wind tunnel test capabilities and developing of test technology from 2020 to 2022 are mainly summarized. Through the development of dual closed-loop adaptive temperature control technology, dual-channel hot-air supply anti-icing test technology, ice shape real-time measurement technology, engine intake accurate simulation technology, rotor icing-aerodynamic load synchronization test technology, etc., simulation capabilities, hot gas anti-icing test capability, ice shape measurement capability, air intake simulation capability, and helicopter rotor icing test capability have been enhanced, and the overall test efficiency has been significantly improved. Finally, the challenges of the large-scale icing wind tunnel tests and the development of the test technology for large supercooled water drops are prospected.

The icing of the aircraft will affect the aerodynamic performance and is the main factor affecting flight safety. Accurate prediction of ice shape can provide strong support for anti-icing work and is of great significance for ensuring flight safety. The traditional numerical icing research methods can hardly meet the requirements of ice accumulation evaluation under multiple icing conditions. Neural network methods provide a robust way for the ice prediction task. The current machine-learning prediction model for airfoil icing can only predict the icing shape of a specific airfoil or a class of airfoils and does not have the universality of icing prediction for a general airfoil. To solve this problem, a deep neural network-based icing prediction method for a general airfoil is proposed, which is suitable for low-speed incompressible flow. The method uses the airfoil pressure coefficient to abstract the characteristics of airfoils, combines the parameters of the flow field and the cloud field as the input, and uses the Fourier series fitting coefficient of the two-dimensional ice curve as the output. By this means, a prediction model using a deep neural network is established, and the icing prediction task of a general airfoil is preliminarily realized. The experimental results of various examples show that the proposed method has a good ice shape prediction effect for a single airfoil or a general airfoil, and the relative error of the main characteristic parameters of the ice shape prediction is not more than 15%.