3D Ice Shape Description Method Based on BLSOM Neural Network

When checking the ice shape calculation software,its accuracy is judged based on the proximity between the calculated ice shape and the typical test ice shape.Therefore,determining the typical test ice shape becomes the key task of the icing wind tunnel tests.In the icing wind tunnel test of the tail wing model of a large amphibious aircraft,in order to obtain accurate typical test ice shape,the Romer Absolute Scanner is used to obtain the 3D point cloud data of the ice shape on the tail wing model.Then,the batch-learning self-organizing map(BLSOM)neural network is used to obtain the 2D average ice shape along the model direction based on the 3D point cloud data of the ice shape,while its tolerance band is calculated using the probabilistic statistical method.The results show that the combination of 2D average ice shape and its tolerance band can represent the 3D characteristics of the test ice shape effectively,which can be used as the typical test ice shape for comparative analysis with the calculated ice shape.

Prediction Model of Aircraft Icing Based on Deep Neural Network

Icing is an important factor threatening aircraft flight safety.According to the requirements of airworthiness regulations,aircraft icing safety assessment is needed to be carried out based on the ice shapes formed under different icing conditions.Due to the complexity of the icing process,the rapid assessment of ice shape remains an important challenge.In this paper,an efficient prediction model of aircraft icing is established based on the deep belief network(DBN)and the stacked auto-encoder(SAE),which are all deep neural networks.The detailed network structures are designed and then the networks are trained according to the samples obtained by the icing numerical computation.After that the model is applied on the ice shape evaluation of NACA0012 airfoil.The results show that the model can accurately capture the nonlinear behavior of aircraft icing and thus make an excellent ice shape prediction.The model provides an important tool for aircraft icing analysis.

Improving flight performance of UAVs by ice shape modulation

Aircraft icing poses a great threat to flight safety.In response to the characteristics of high-power consumption,large volume,and heavy weight of traditional anti-/de-icing technologies,the concept of ice shape modulation is proposed,which is called ice tolerant flight.Firstly,the flight performance of Unmanned Aerial Vehicle(UAV)was compared in three states:no ice,full ice,and modulated ice through flight tests.It was found that ice shape modulation has a significant improvement effect on the aerodynamic performance of aircraft under icing conditions.Under the three modulated ice shape conditions in this experiment,the lift coefficient of the UAV under different ice shape modulation conditions increased by 18%–33%,and the stalling angle was delayed by 3°-5°.Subsequently,the pressure distribution,streamlines in the flow field,and detached vortex distribution of the UAV model in these three states were obtained through numerical simulation,to study the mechanism of ice shape modulation on the aerodynamic performance of aircraft.The simulation found that the reason for the improvement of the wings effect after ice shape modulation is that the modulated area forms a leading-edge protrusion structure similar to a vortex generator.This structure prolongs the mixed flow region on the wings surface and reduces the trend of flow separation,which plays a role in increasing lift and reducing drag for UAVs under icing conditions.Finally,a reverse reachable set that can be used for unexpected state recovery is used as the definition of flight safety boundaries,and an aircraft dynamics model is established to obtain flight safety boundaries for different states.Research has found that the flight safety boundary of the UAV in a no ice state is greater than that in a modulated ice state,and the safety boundary in a modulated ice state is greater than that in a full ice state.Compared with the full ice state,the flight safety boundary after modulation has expanded by 27.0%.The scheme of ice shape modulation can provide a basis for the flight safety of aircraft under icing conditions.

Improving aircraft aerodynamic performance with bionic wing obtained by ice shape modulation

For Unmanned Aerial Vehicles(UAVs)with limited electrical power to achieve effectively anti-/de-icing at the leading edge of the wing,a strategy of ice shape modulation was proposed.Isolated simulated ice shape pieces printed by 3D printing technology are mounted on a NACA0012 finite wing model,and its lift/drag coefficients and suction-side velocity fields are measured by the six-component force balance and the Particle Imaging Velocimetry(PIV),respectively.The ratio of the spanwise length of a single ice shape piece to chord length and the spanwise length of the non-icing area between the two adjacent single ice shape pieces are defined as dimensionless ice shape length(w/c)and dimensionless modulation ratio(w/λ),respectively.The results indicate that for a fixed w/λ,the wing lift coefficient first increases and then drops with increasing w/c,and a peak value exists when w/c is between 0.1 and 0.2.The lower the w/λis,the higher the wing lift coefficient will be.The periodical variation of the flow separation area along the spanwise direction is attributed on the one hand to the acceleration effect of the flow field in the non-icing area which reduces the separation area,and on the other hand to the cross-flow caused by the streamwise vortices from the non-icing area to the icing area which promotes the mixing of the flow field(similar to vortex generators).The obtained modulation law is verified through flight tests and provides guidance for the use of ice shape modulation scheme for UAVs that cannot be completely anti-/deicing under severe weather conditions.