Study On Thermal Shock Damage Effect Of Pavement Surface By Heat-wind Snow Removal

Heat-wind snow removal became the most effective method of fast recovery the flight after winter snowfall and icing, however, the heat wind quickly removed ice and snow on the concrete surface as well as brought very serious local injury, it could not be ignored. Especially in the more frequent snowfall Three- North regional Airport, on the basis of the fast snow removal, to minimize the extent of damage was necessary. To explore methods to reduce pavement damage because of de-icing, or to increase the resistance to heat-wind shocks, according to the thermal properties of concrete materials, pavement structure characteristics such as thermal shock effects, analyzed physical and mechanical response behavior laws of pavement on the role of high temperature air shock, builded a theoretical analytical expression models to express pavement damage and the cumulative process of damage. Based on the principle of thermal shock damage of concrete pavement, for the characteristics of the surface damage, finite element simulated the damage effect and designed lab research to simulate airport pavement heat-wind removal snow. Based on theoretical analysis and experimental results, parameters conversion method of using neural network model to predict its damage effects were discussed and proposed forecast evaluation method of pavement damage effects, based on neural network theory.Theoretical analysis showed that the characteristics of high-temperature air shocks damage for cement concrete pavement could be equivalent to the heat wave shock effects, and analyzed the heat transfer law in the pavement surface and tress concentration phenomenon momentarily, finally, established exponential model to characterization the relationship between the damage and shock times. Finite element analysis results showed that, NEWMARK method could solve transient heat conduction equation to simulation damage evolution process of pavement.Lab studies showed that, baced on energy point of view, by changing the different performance parameters involved in thermal shock fracture factor could analyze or improve thermal shock resistance of concrete pavement, thereby to reduce the extent of damage in the process of snow removal on the pavement. For frequent snowfall airports, pavement damage prediction and the future of safe life, could make use of neural network theory, using a limited number of experimental test data to bypass the complex affected variable, based on the exponential model and improved B-P algorithm, to provide a more scientific methods and means to guide engineering practice.