Abstract

The void at the bottom of a cement concrete slab is a common problem of composite pavements. It is of great significance to evaluate the spring stiffness, void size, and soil base elastic modulus at the bottom of cement concrete slab timely and accurately for the maintenance and guarantee of the pavement performance. In this paper, the composite pavement at a joint is modeled and the load transfer mechanism is realized by using spring groups for simulating the dowels that connect the two slabs of the joint. A database is established based on a large number of simulation results of joint load transfer efficiency and voids and the changing law of load transfer efficiency of cement concrete slab reveals their relationship. Taking into consideration the spring stiffness, void size, and soil base elastic modulus, the void evalua\tion method of composite pavement cement concrete slab is established by using back propagation neural network algorithm. The results show that the void evaluation method can provide the void determination map with two parameters. The values of the two parameters can be determined by the deflection basin. After querying the Atlas, the void determination can be more accurate. The research results provide scientific guidance for the void identification of the composite pavement and can effectively extend the service life of the pavement.

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