Cement Concrete Pavement Maintenance Management System Based On MEPDG In Seasonal Frozen Regions

Cement concrete pavements will have various types of diseases with the increase of service life and the number of traffic loads.The disease of cement concrete pavement in the cold season with low temperature and snowy and extreme climate has its particularity.There have been many reports on the impact of climate change on cement concrete pavement.The technical status assessment of highway cement concrete pavement has also been standardized,but the research results of the technical status evaluation of cement concrete pavement in the seasonal frozen regions under extreme climatic conditions have rarely been reported.In order to reflect the extreme climatic characteristics,the evaluation index system for the technical status of cement concrete pavement in the seasonal frozen regions was supplemented,and the maintenance management system suitable for the cement concrete pavement in the seasonal frozen regions was established.Seven typical cement concrete pavement roads in the seasonal frozen regions were selected.The technical status was tested and analyzed,and the traffic volume,climatic conditions,pavement performance and structural performance of the road sections were investigated.The existing deficiencies of the technical indicators of cement concrete pavement were analyzed.The research proposed the evaluation index applicable to the seasonal frozen regions.The influence of the void position of the pavement,the void regions and the depth of the void on the deformation of the concrete slab is analyzed by finite element analysis.The difference of the deflection between the edge and the plate,the angle of the plate and the plate are studied under different transfer capacity and void area.In the middle of the bend difference,the relationship between the deflection difference and the bottom of the road panel is analyzed,and the indoor simulation test and the on-site core sampling are used for verification.The SOM neural network was created by MATLAB.The road surface technical status index of the typical road section in the seasonal frozen regions was used as the training sample and identification sample of the SOM neural network.The samples were normalized and the network including the training steps and the learning rate were adjusted.Research to determine the best weight of the evaluation indicators;Based on the MEPDG theory,the climate and traffic volume are used as important parameters to correct the IRI prediction model weights,The correlation between the dependent variable DBL and the independent variables CRK and SF is performed,regression analysis is performed,a prediction model is established,and the established model is verified;Use the language of HTML,CSS,javaScrip and jQuery to research and develop the road maintenance management system with functions such as data input,road performance prediction,road surface condition evaluation,maintenance and report processing.The research results show that when one or several indicators in PCI,RQI and SRI are in the poor,it indicates that the pavement structure is seriously damaged.Only the performance index can not reflect the actual road surface technology.Based on the existing evaluation system,the three structural performance indexes of bottom voiding,transfer capacity and structural strength are used to evaluate the technical status of cement concrete pavement in the seasonal frozen regions,which is more in line with the actual situation.For the different load carrying capacity of cement concrete slabs,the drop hammer type deflection instrument is proposed.The test results determine the standard of voiding of cement concrete slab in the seasonal frozen regions;The weight of each indicator of the pavement technical condition assessment model in the seasonal frozen regions after the structural performance evaluation index is determined by SOM neural network training,the PCI is 0.36,RQI is 0.29,the SRI is 0.08,the PSSI is 0.08,the TK is 0.07,and the KJ is 0.12.Using the SPSS software,the IRI modified prediction model and the DBL prediction model are established.The deterministic coefficient variance contribution rate of the model is above 90%,indicating that the degree of fitting is high,the empirical residuals and regression normalized residuals of the two models are in accordance with the normal distribution,and the prediction results of the new model are obtained better than existing models.Developed a concrete and concrete pavement maintenance management system with simple operation in the seasonal frozen regions,friendly interface and complete functions,which can determine reasonable maintenance timing and applicable maintenance countermeasures.The research results can provide effective technical support for the maintenance and management of cement concrete pavement in the seasonal frozen regions,and they have practical application value.