Study On Mixture Proportion Design And Performance Prediction Of High Performance Road Rubber Concrete

With the increase of citizens' demand for materials,the transportation business is increasing,the frequency of freight vehicles on the road is increasing rapidly.In order to improve transportation efficiency,overload phenomenon is very common.The existing cement concrete pavement has low durability and poor toughness.Under the action of overloaded vehicles,damage occurs prematurely when the design service life is not reached,resulting in safety hazards.Crumb Rubber Concrete(CRC)has good toughness and deformation properties.At the same time,the material has excellent wear resistance and good frost resistance.It is an ideal material for pavement construction.However,the strength of the concrete is reduced after the rubber aggregate is mixed.Under the action of heavy load and overloaded vehicles,the damage will still occur due to the low strength.In order to adapt rubber concrete to heavy traffic,it is necessary to prepare rubber concrete with high strength,good toughness and good durability,namely High Performance Crumb Rubber Concrete(HP-CRC).In this paper,according to the orthogonal test scheme,CRC materials with different water-cement ratio,rubber content,rubber particle size and different fly ash content were prepared.The compressive strength,flexural strength and elastic modulus were tested by experiment.The method analyzes the test results,and obtains the order of influence of various factors on CRC compressive strength,flexural strength and elastic modulus,and optimizes the performance of high-performance rubber concrete.In the construction of BP neural network model,four factors in orthogonal experiment were used as input variables to predict the mechanical properties of HP-CRC after optimization,and the experimental results were compared to the experimental results of HP-CRC mechanical properties,test results and prediction results.Match.On this basis,the experimental research on the frost resistance,chloride ion permeability and wear resistance of HP-CRC and ordinary concrete were carried out,when the rubber content reached 10%,the durability of concrete could be improved significantly.And the durability of HP-CRC was analyzed by AHP analytic method.The results show that the HP-CRC has better road performance and is more suitable as a heavy traffic pavement material.The mechanical properties of HP-CRC meet the needs of heavy-duty traffic pavement materials,and its durability is superior to that of ordinary concrete pavement materials.When the water-cement ratio is controlled between 0.30 and 0.35,the rubber content is between 10% and 15%.When the particle size is 50 mesh-80 mesh and the fly ash content is less than 10%,the toughness of the concrete can be effectively improved under the requirement of heavy-duty traffic conditions for the mechanical properties of the pavement material,and the durability of the concrete can be improved.Life expectancy is extended.The application of the orthogonal-BP neural network prediction system can greatly reduce the test cost,save manpower and material resources to efficiently predict the material properties of different mix ratio parameters,and quickly select the appropriate HP-CRC mix ratio parameters according to the construction conditions,increase work productivity.