A novel approach of jet polishing for interior surface of small-grooved components using three developed setups

It is a challenge to polish the interior surface of an additively manufactured component with complex structures and groove sizes less than 1 mm.Traditional polishing methods are disabled to polish the component,meanwhile keeping the structure intact.To overcome this challenge,small-grooved components made of aluminum alloy with sizes less than 1 mm were fabricated by a custom-made printer.A novel approach to multi-phase jet(MPJ)polishing is proposed,utilizing a self-developed polisher that incorporates solid,liquid,and gas phases.In contrast,abrasive air jet(AAJ)polishing is recommended,employing a customized polisher that combines solid and gas phases.After jet polishing,surface roughness(Sa)on the interior surface of grooves decreases from pristine 8.596μm to 0.701μm and 0.336μm via AAJ polishing and MPJ polishing,respectively,and Sa reduces 92%and 96%,correspondingly.Furthermore,a formula defining the relationship between linear energy density and unit defect volume has been developed.The optimized parameters in additive manufacturing are that linear energy density varies from 0.135 J mm^(-1)to 0.22 J mm^(-1).The unit area defect volume achieved via the optimized parameters decreases to 1/12 of that achieved via non-optimized ones.Computational fluid dynamics simulation results reveal that material is removed by shear stress,and the alumina abrasives experience multiple collisions with the defects on the heat pipe groove,resulting in uniform material removal.This is in good agreement with the experimental results.The novel proposed setups,approach,and findings provide new insights into manufacturing complex-structured components,polishing the small-grooved structure,and keeping it unbroken.

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.

Effect of preload force on heat generation of fatigue crack in ultrasonic infrared thermography

The heat generation behaviors of fatigue crack are deeply investigated under different preload forces combing numerical simulation and experiment.Firstly,a multi-contact simulation model is applied to stimulate the crack surfaces contact and the horn-sample contact under ultrasonic excitation for calculating the temperature fields.Then,the ultrasonic infrared thermography testing and the microscope testing are carried out for the heat generation and the plastic deformation behaviors of crack region under different preload forces.On this basis,an indirect observation method based on dots distribution is proposed to estimate the plastic deformation on crack contact surfaces.The obtained results show that the temperature rise of crack region increases with the increase of preload force when the preload force is less than 250 N,while the temperature rise rapidly declines due to the plastic deformation on crack contact surfaces and the inhibition effect when the preload force is 280 N.Moreover,the plastic deformation does not lead to the crack propagation,but reduces the detection repeatability of fatigue crack.This work provides an effective method for optimizing testing conditions in practical testing processes,which will be helpful to the establishment of testing standards for batches of test objects in ultrasonic infrared thermography testing.

Progress in application of CFD techniques

Computational Fluid Dynamics (CFD) is an important branch of fluid mechanics, and will continue to play great roles on the design of aerospace vehicles, explora- tion of new concept vehicles and new aerodynamic technology. This paper will present the progress of CFD from point of view of engineering application in recent years at CARDC, including the software integration, grid technique, speeding up of convergence, unsteady fluid computation,etc., and also give some engineering application examples of CFD at CARDC.