Research On Dynamic Response Of Airport Rigid Pavement And Backcalcuation Method Of Structural Layer Modulus

The structural performance of the airport’s rigid pavement will be attenuated during use.To ensure flight safety and performance,it needs to be regularly evaluated.The reaction modulus of the soil foundation and the top surface of the base is two important indicators to characterize the structural performance.At present,Falling weight deflectometer,FWD has become the main equipment for evaluating the performance of the rigid pavement structure of the airport due to its advantages such as rapid and losslessness compared with traditional methods.However,the reaction modulus of the soil foundation and the top surface of the base layer cannot be directly derived from the deflection basin data measured by FWD,instead,backcalculating using the deflection basin is needed.At present,there are many researches on modulus backcalculation methods,and these methods have their own advantages and disadvantages.This article intends to propose a new backcalculation method,to make the results of backcalculation more accurate.For this,this paper will use the method of finite element numerical simulation to establish a mechanical response calculation model of the typical airport’s rigid pavement structure under the FWD dynamic load,to study different factors influencing the deflection basin of the pavement structure under FWD load under different working conditions,to establish the mapping relationship between the deflection basin and the pavement structure,the deflection basin parameters most closely related to the pavement structure layer modulus are selected as the backcalculation index,and a backcalculation method of structural layer modulus based on BP neural network is established.The main research contents of this article are as follows:Firstly,the ABAQUS finite element analysis software is used to establish the mechanical response calculation model of the airport rigid pavement structure under FWD dynamic loads,and the analysis of the factors of the airport rigid pavement structure influencing the deflection basin is carried out.The results show that the presence of temperature warping deformation of the pavement slab will affect the accuracy of the deflection basin data and backcalculation of the pavement structure.Therefore,when performing dynamic response analysis and backcalculation of the structural layer modulus,the temperature warpage of the pavement slab should be taken into consideration.On the basis of the above,it is proposed to classify the deflection basin according to the warping condition of the pavement slab,and analyze the change rule of the pavement slab deflection basin with various influencing factors under different temperature warping states;Secondly,the parameters of deflection basin and modulus of pavement structure layer suitable for backcalculation are selected as back calculation ind exes.In the study,the equivalent elastic modulus of the top surface of the base layer is selected as the characteristic parameter of the modulus of the pavement structure layer.When temperature warpage is not considered,the deflection value is selected as the deflection basin parameter for backcalculation according to the correlation analysis;When the panel is under a negative temperature gradient,the deflection value is corrected and used as backcalculation indexes;when the panel is under a positive temperature gradient,the penetration of the road panel corner is proposed as an evaluation index;Finally,based on the BP neural network,the backcalculation method of the rigid pavement structure layer modulus is established.Us e the deflection basin data obtained in the dynamic response analysis as the training sample of the neural network,use the neural network toolbox to backcalculate,and choose different parameters as input variables for different temperature gradients.The results show that the trained neural network can meet the accuracy requirements.The neural network is used to backcalculate the actual deflection basin,and the results are consistent with the results of the road surface survey,which further verified the effectiveness of the method.